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DeepSeek Revives China's Tech Industry, Challenging Western Giants

As a result of DeepSeek's emergence, the global landscape for artificial intelligence (AI) has been profoundly affected, going way beyond initial media coverage. AI-driven businesses, semiconductor manufacturing, data centres and energy infrastructure all benefit from its advancements, which are transforming the dynamics of the industry and impacting valuations across key sectors.

DeepSeek's R1 model is one of the defining characteristics of its success, and it represents one of the technological milestones of the company. This breakthrough system can rival leading Western artificial intelligence models while using significantly fewer resources to operate. Despite conventional assumptions that Western dominance in artificial intelligence remains, Chinese R1 models demonstrate China's growing capacity to compete at the highest level of innovation at the highest levels in AI.

The R1 model is both efficient and sophisticated. Among the many disruptive forces in artificial intelligence, DeepSeek has established itself as one of the most efficient, scalable, and cost-effective systems on the market. It is built on a Mixture of Experts (MoE) architecture, which optimizes resource allocation by utilizing only relevant subnetworks to enhance performance and reduce computational costs at the same time.

DeepSeek's innovation places it at the forefront of a global AI race, challenging Western dominance and influencing industry trends, investment strategies, and geopolitical competition while influencing industry trends. Even though its impact has spanned a wide range of industries, from technology and finance to energy, there is no doubt that a shift toward a decentralized AI ecosystem has taken place.

As a result of DeepSeek's accomplishments, a turning point has been reached in the development of artificial intelligence worldwide, emphasizing the fact that China is capable of rivalling and even surpassing established technological leaders in certain fields. There is a shift indicating the emergence of a decentralized AI ecosystem in which innovation is increasingly spread throughout multiple regions rather than being concentrated in Western markets alone.

Changing power balances in artificial intelligence research, commercialization, and industrial applications are likely to be altered as a result of the intensifying competition that is likely to persist. China's technology industry has experienced a wave of rapid innovation as a result of the emergence of DeepSeek as one of the most formidable competitors in artificial intelligence (AI). As a result of DeepSeek’s alleged victory over OpenAI last January, leading Chinese companies have launched several AI-based solutions based on a cost-effective artificial intelligence model developed at a fraction of conventional costs.

The surge in artificial intelligence development poses a direct threat to both OpenAI and Alphabet Inc.’s Google, as well as the greater AI ecosystem that exists in Western nations. Over the past two weeks, major Chinese companies have unveiled no less than ten significant AI products or upgrades, demonstrating a strong commitment to redefining global AI competition. In addition to DeepSeek's technological achievements, this rapid succession of advancements was not simply a reaction to that achievement, but rather a concerted effort to set new standards for the global AI community.

According to Baidu Inc., it has launched a new product called the Ernie X1 as a direct rival to DeepSeek's R1, while Alibaba Group Holding Ltd has announced several enhancements to its artificial intelligence reasoning model. At the same time, Tencent Holdings Ltd. has revealed its strategic AI roadmap, presenting its own alternative to the R1 model, and Ant Group Co. has revealed research that indicated domestically produced chips can be used to cut costs by up to 20 per cent.

A new version of DeepSeek was unveiled by DeepSeek, a company that continues to grow, while Meituan, a company widely recognized as being the world's largest meal delivery platform, has made significant investment in artificial intelligence. As China has become increasingly reliant on open-source artificial intelligence development, established Western technology companies are being pressured to reassess their business strategies as a result.

According to OpenAI, as a response to DeepSeek’s success, the company is considering a hybrid approach that may include freeing up certain technologies, while at the same time contemplating substantial increases in prices for its most advanced artificial intelligence models. There is also a chance that the widespread adoption of cost-effective AI solutions could have profound effects on the semiconductor industry in general, potentially hurting Nvidia's profits as well.

Analysts expect that as DeepSeek's economic AI model gains traction, it may become inevitable that leading AI chip manufacturers' valuations are adjusted. Chinese artificial intelligence innovation is on the rise at a rapid pace, underscoring a fundamental shift in the global technology landscape. In the world of artificial intelligence, Chinese firms are increasingly asserting their dominance, while Western firms are facing mounting challenges in maintaining their dominance.

As the long-term consequences of this shift remain undefined, the current competitive dynamic within China's AI sector indicates an emerging competitive dynamic that could potentially reshape the future of artificial intelligence worldwide. The advancements in task distribution and processing of DeepSeek have allowed it to introduce a highly cost-effective way to deploy artificial intelligence (AI). Using computational efficiency, the company was able to develop its AI model for around $5.6 million, a substantial savings compared to the $100 million or more that Western competitors typically require to develop a similar AI model.

By introducing a resource-efficient and sustainable alternative to traditional models of artificial intelligence, this breakthrough has the potential to redefine the economic landscape of artificial intelligence. As a result of its ability to minimize reliance on high-performance computing resources, DeepSeekcano reduces costs by reducing the number of graphics processing units (GPUs) used. As a result, the model operates with a reduced number of graphics processing unit (GPU) hours, resulting in a significant reduction in hardware and energy consumption.

Although the United States has continued to place sanctions against microchips, restricting China's access to advanced semiconductor technologies, DeepSeek has managed to overcome these obstacles by using innovative technological solutions. It is through this resilience that we can demonstrate that, even in challenging regulatory and technological environments, it is possible to continue to develop artificial intelligence. DeepSeek's cost-effective approach influences the broader market trends beyond AI development, and it has been shown to have an impact beyond AI development.

During the last few years, a decline in the share price of Nvidia, one of the leading manufacturers of artificial intelligence chips, has occurred as a result of the move toward lower-cost computation. It is because of this market adjustment, which Apple was able to regain its position as the world's most valuable company by market capitalization. The impact of DeepSeek's innovations extends beyond financial markets, as its AI model requires fewer computations and operates with a lower level of data input, so it does not rely on expensive computers and big data centres to function.

The result of this is not only a lower infrastructure cost but also a lower electricity consumption, which makes AI deployments more energy-efficient. As AI-driven industries continue to evolve, DeepSeek's model may catalyze a broader shift toward more sustainable, cost-effective AI solutions. The rapid advancement of technology in China has gone far beyond just participating in the DeepSeek trend. The AI models developed by Chinese developers, which are largely open-source, are collectively positioned as a concerted effort to set global benchmarks and gain a larger share of the international market.

Even though it is still unclear whether or not these innovations will ultimately surpass the capabilities of the Western counterparts of these innovations, a significant amount of pressure is being exerted on the business models of the leading technology companies in the United States as a result of them. It is for this reason that OpenAI is attempting to maintain a strategic balance in its work. As a result, the company is contemplating the possibility of releasing certain aspects of its technology as open-source software, as inspired by DeepSeek's success with open-source software.

Furthermore, it may also contemplate charging higher fees for its most advanced services and products. ASeveralindustry analysts, including Amr Awadallah, the founder and CEO of Vectara Inc., advocate the spread of DeepSeek's cost-effective model. If premium chip manufacturers, such as Nvidia, are adversely affected by this trend,theyt will likely have to adjust market valuations, causing premium chip manufacturers to lose profit margins.

Alibaba Launches Latest Open-source AI Model from Qwen Series for ‘Cost-effective AI agents’

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Alibaba Launches Latest Open-source AI Model from Qwen Series for ‘Cost-effective AI agents’

Alibaba Launches Lates Open-source AI Model from Qwen Series for ‘Cost-effective AI agents’

Last week, Alibaba Cloud launched its latest AI model in its “Qwen series,” as large language model (LLM) competition in China continues to intensify after the launch of famous “DeepSeek” AI.

The latest "Qwen2.5-Omni-7B" is a multimodal model- it can process inputs like audio/video, text, and images- while also creating real-time text and natural speech responses, Alibaba’s cloud website reports. It also said that the model can be used on edge devices such as smartphones, providing higher efficiency without giving up on performance.

According to Alibaba, the “unique combination makes it the perfect foundation for developing agile, cost-effective AI agents that deliver tangible value, especially intelligent voice applications.” For instance, the AI can be used to assist visually impaired individuals to navigate their environment via real-time audio description.

The latest model is open-sourced on forums GitHub and Hugging Face, after a rising trend in China post DeepSeek breakthrough R1 model open-source. Open-source means a software in which the source code is created freely on web for potential modification and redistribution.

In recent years, Alibaba claims it has open-sourced more that 200 generative AI models. In the noise of China’s AI dominance intensified by DeepSeek due to its shoe string budget and capabilities, Alibaba and genAI competitors are also releasing new, cost-cutting models and services an exceptional case.

Last week, Chinese tech mammoth Baidu launched a new multimodal foundational model and its first reasoning-based model. Likewise, Alibaba introduced its updated Qwen 2.5 AI model in January and also launched a new variant of its AI assistant tool Quark this month.

Alibaba has also made strong commitments to its AI plan, recently, it announced a plan to put $53 billion in its cloud computing and AI infrastructure over the next three years, even surpassing its spending in the space over the past decade.

CNBC talked with Kai Wang, Asia Senior equity analyst at Morningstar, Mr Kai told CNBC that “large Chinese tech players such as Alibaba, which build data centers to meet the computing needs of AI in addition to building their own LLMs, are well positioned to benefit from China's post-DeepSeek AI boom.” According to CNBC, “Alibaba secured a major win for its AI business last month when it confirmed that the company was partnering with Apple to roll out AI integration for iPhones sold in China.”

Gmail Upgrade Announced by Google with Three Billion Users Affected

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Cyberhackers Cybersecurity CyberThreat Gmail Google Google Drive Google Meet Technology

Gmail Upgrade Announced by Google with Three Billion Users Affected

The Google team has officially announced the launch of a major update to Gmail, which will enhance functionality, improve the user experience, and strengthen security. It is anticipated that this update to one of the world’s most commonly used email platforms will have a significant impact on both individuals as well as businesses, providing a more seamless, efficient, and secure way to manage digital communications for individuals and businesses alike.

The Gmail email service, which was founded in 2004 and has consistently revolutionized the email industry with its extensive storage, advanced features, and intuitive interface, has continuously revolutionized the email industry. In recent years, it has grown its capabilities by integrating with Google Drive, Google Chat, and Google Meet, thus strengthening its position within the larger Google Workspace ecosystem by extending its capabilities.

The recent advancements from Google reflect the company’s commitment to innovation and leadership in the digital communication technology sector, particularly as the competitive pressures intensify in the email and productivity services sector. Privacy remains a crucial concern as the digital world continues to evolve. Google has stressed the company’s commitment to safeguarding user data, and is ensuring that user privacy remains of the utmost importance.

In a statement released by the company, it was stated that the new tool could be managed through personalization settings, so users would be able to customize their experience according to their preferences, allowing them to tailor their experience accordingly.

However, industry experts suggest that users check their settings carefully to ensure their data is handled in a manner that aligns with their privacy expectations, despite these assurances. Those who are seeking to gain a greater sense of control over their personal information may find it prudent to disable AI training features. In particular, this measured approach is indicative of broader discussions regarding the trade-off between advanced functionality and data privacy, especially as the competition from Microsoft and other major technology companies continues to gain ground.

Increasingly, AI-powered services are analyzing user data and this has raised concerns about privacy and data security, which has led to a rise in privacy concerns. Chrome search histories, for example, offer highly personal insights into a person’s search patterns, as well as how those searches are phrased. As long as users grant permission to use historical data, the integration of AI will allow the company to utilize this historical data to create a better user experience.

It is also important to remember, however, that this technology is not simply a tool for executive assistants, but rather an extremely sophisticated platform that is operated by one of the largest digital marketing companies in the world. In the same vein, Microsoft's recent approach to integrating artificial intelligence with its services has created a controversy about user consent and data access, leading users to exercise caution and remain vigilant.

According to PC World, Copilot AI, the company's software for analyzing files stored on OneDrive, now has an automatic opt-in option. Users may not have been aware that this feature, introduced a few months ago, allowed them to consent to its use before the change. It has been assured that users will have full Although users have over their data they have AI-driven access to cloud-stored files, the transparency of such integrations is s being questioned as well as the extent of their data. There remain many concerns among businesses that are still being questioned. Businesses remain concerned aboutness, specifically about privacy issues.

The results of Global Data (cited by Verdict) indicate that more than 75% of organizations are concerned about these risks, contributing to a slowdown in the adoption of artificial intelligence. A study also indicates that 59% of organizations lack confidence in integrating artificial intelligence into their operations, with only 21% reporting an extensive or very extensive deployment of artificial intelligence.

In the same way that individual users struggle to keep up with the rapid evolution of artificial intelligence technologies, businesses are often unaware of the security and privacy threats that these innovations pose. As a consequence, industry experts advise organizations to prioritize governance and control mechanisms before adopting AI-based solutions to maintain control over their data. CISOs (chief information security officers) might need to adopt a more cautious approach to mitigate potential risks, such as restricting AI adoption until comprehensive safeguards have been implemented.

The introduction of AI-powered innovations is often presented as seamless and efficient tools, but they are supported by extensive frameworks for collecting and analyzing data. For these systems to work effectively, they must have well-defined policies in place that protect sensitive data from being exposed or misused. As AI adoption continues to grow, the importance of stringent regulation and corporate oversight will only increase.

To improve the usability, security and efficiency of Gmail, as well as make it easier for both individuals and businesses, Google's latest update has been introduced to the Gmail platform. There are several features included in this update, including AI-driven features, improved interfaces, and improved search capabilities, which will streamline email management and strengthen security against cybersecurity threats.

By integrating Google Workspace deeper, businesses will benefit from improved security measures that safeguard sensitive information while enabling teams to work more efficiently and effectively. This will allow businesses to collaborate more seamlessly while reducing cybersecurity risks. The improvements added by Google to Gmail allow it to be a critical tool within corporate environments, enhancing productivity, communication, and teamwork. With this update, Google confirms Gmail's reputation as a leading email and productivity tool.

In addition to optimizing the user experience, integrating intelligent automation, strengthening security protocols, and expanding collaborative features, the platform maintains its position as a leading digital communication platform. During the rollout over the coming months, users can expect a more robust and secure email environment that keeps pace with the changing demands of today's digital interactions as the rollout progresses.

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AI and Privacy – Issues and Challenges

Artificial intelligence is changing cybersecurity and digital privacy. It promises better security but also raises concerns about ethical boundaries, data exploitation, and spying. From facial recognition software to predictive crime prevention, customers are left wondering where to draw the line between safety and overreach as AI-driven systems become more and more integrated into daily life.

The same artificial intelligence (AI) tools that aid in spotting online threats, optimising security procedures, and stopping fraud can also be used for intrusive data collecting, behavioural tracking, and mass spying. The use of AI-powered surveillance in corporate data mining, law enforcement profiling, and government tracking has drawn criticism in recent years. AI runs the potential of undermining rather than defending basic rights in the absence of clear regulations and transparency.

AI and data ethics

Despite encouraging developments, there are numerous instances of AI-driven inventions going awry, which raise serious questions. A face recognition business called Clearview AI amassed one of the largest facial recognition databases in the world by illegally scraping billions of photos from social media. Clearview's technology was employed by governments and law enforcement organisations across the globe, leading to legal action and regulatory action about mass surveillance.

The UK Department for Work and Pensions used an AI system to detect welfare fraud. An internal investigation suggested that the system disproportionately targeted people based on their age, handicap, marital status, and country. This prejudice resulted in certain groups being unfairly picked for fraud investigations, raising questions about discrimination and the ethical use of artificial intelligence in public services. Despite earlier guarantees of impartiality, the findings have fuelled calls for increased openness and supervision in government AI use.

Regulations and consumer protection

The ethical use of AI is being regulated by governments worldwide, with a number of significant regulations having an immediate impact on consumers. The AI Act of the European Union, which is scheduled to go into force in 2025, divides AI applications into risk categories.

Strict regulations will be applied to high-risk technology, like biometric surveillance and facial recognition, to guarantee transparency and moral deployment. The EU's commitment to responsible AI governance is further reinforced by the possibility of severe sanctions for non compliant companies.

Individuals in the United States have more control over their personal data according to California's Consumer Privacy Act. Consumers have the right to know what information firms gather about them, to seek its erasure, and to opt out of data sales. This rule adds an important layer of privacy protection in an era where AI-powered data processing is becoming more common.

The White House has recently introduced the AI Bill of Rights, a framework aimed at encouraging responsible AI practices. While not legally enforceable, it emphasises the need of privacy, transparency, and algorithmic fairness, pointing to a larger push for ethical AI development in policy making.

The Future of Cloud Ownership Amid Deglobalization

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The Future of Cloud Ownership Amid Deglobalization

Modern digital landscapes have become increasingly challenging for data management because of the rapid expansion of data volumes and sources. Organizations have to navigate the complexities of storing a vast amount of data while ensuring seamless access for a variety of users, regardless of their location in the world. It has become increasingly important to manage data efficiently due to the increased demand for real-time data availability and the need to maintain stringent security measures.

The growing need for real-time data availability has resulted in the need for efficient data management. Many enterprises are turning to cloud computing as a reliable solution to address these challenges. Cloud-based systems offer the flexibility needed to accommodate diverse access needs while maintaining the integrity and security of the data. A business can streamline its operation, improve collaboration, and develop scalable data management strategies tailored to the needs of its customers by leveraging cloud technologies.

To make the most of cloud services, a comprehensive understanding of cloud data management principles is needed to effectively utilize cloud services for complex business needs. To maximize the benefits of cloud solutions, it is essential to maintain knowledge of industry best practices, adopt advanced security measures, and learn from successful implementations in order to maximize their potential. In a world where organizations are constantly embracing digital transformation, the cloud remains one of the most effective and efficient ways to manage data while ensuring efficiency, security, and long-term sustainability.

According to a comprehensive analysis of global trends, a noticeable shift has been witnessed toward conservative governance and a retreat from globalization. Increasingly, nations are emphasizing self-reliance as a result of economic, security, and social concerns. In order to reduce dependency on foreign entities, they are concentrating on strengthening their domestic industries. In this sense, this transition reflects a wider trend towards economic nationalism, in which governments seek to preserve their interests by utilizing their local resources and capabilities in order to protect themselves.

Among the many challenges faced by this shift in data management and cloud computing are infrastructure, security, and accessibility issues that are very important. It is important to understand that even though the cloud is perceived by many as a borderless, abstract entity, it is fundamentally based on physical data centres strategically located across the globe. Organizations carefully select these data centers to enhance performance, decrease latency, and deliver seamless service by placing data closer to end users.

A key challenge for businesses and policy makers as deglobalization takes hold is balancing the need for efficiency with evolving regulatory and geopolitical constraints, as well as the increasing need for deglobalization to succeed. The ability to maintain the integrity, security, and compliance of data in cloud environments requires effective cloud data governance. As a result of this framework, data collection, storage, protection, and utilization across various cloud platforms are overseen by a set of structured policies, regulations, and procedures.

By implementing the combination of best practices and advanced technologies, organizations can ensure that the quality and security of their data are maintained regardless of the physical location in which the information is stored or the cloud provider in which it is hosted. In the context of cloud data governance, the primary objective is to enhance the security of the data by enforcing stringent access controls, encryption protocols, and continuous auditing measures, which are designed to enhance data security.

Cloud-based infrastructures have become increasingly popular as they distribute data across multiple locations, and safeguarding sensitive data from unauthorized access, breaches, and cyber threats becomes progressively more important. Besides ensuring the protection of organizational assets, strong security policies foster trust among customers and stakeholders. Additionally, regulation compliance remains a fundamental aspect of cloud data governance. Among all the companies operating across many industries and jurisdictions, a wide range of laws are important to follow, such as GDPR, CCPA, and HIPAA. With a well-defined governance framework, companies are able to navigate the complex world of global regulatory requirements, ensuring that all data management practices are aligned with legal and industry specific standards so they are not exposed to legal and regulatory penalties.

In this increasingly data-driven world, companies can reduce risks, avoid legal penalties, and enhance operational efficiency by integrating compliance strategies into cloud governance policies. An interconnected global economy traditionally relies on cross-border infrastructures for data storage and management. Nations typically store and access information through data centers located in other countries, resulting in an efficient data flow by minimizing latency and optimizing data flow that enables data to be stored and accessed.

Several companies in Europe might not use servers based in Oceania due to performance restrictions, but instead host data at intermediary locations in Southeast Asia in order to improve speed and reduce latency. However, recent geopolitical developments have begun to reshape how cloud data infrastructures are constructed. A number of international conflicts, especially after the beginning of the Ukrainian conflict, have emphasized the vulnerability of businesses that rely on foreign cloud services. As a result of sanctions imposed by the United States and allied nations on Russia, businesses operating in the region have had to rethink their dependence on data.

Other nations were prompted to take notice of the risks associated with relying on foreign digital infrastructure, which raised pressing concerns among them. A larger issue of data sovereignty has been raised as a result of these uncertainties. Relying on cloud infrastructure from a foreign country not only exposes companies and governments to potential sanctions but also imposes varying data privacy and security requirements on their business operations. As a result of this recognition of these risks, many nations have begun to prioritize the importance of self-reliance in data management, aiming to gain a greater sense of control over their digital assets through self-reliance.

As a result of this shift towards localized cloud infrastructure, national data is being protected against external influences, regulatory risks are mitigated, and a long-term digital resilience is being strengthened. There has been a dramatic shift in the landscape of data management, from traditional, locally hosted storage solutions to more dynamic, scalable cloud-based frameworks that are becoming more popular.

The industry standard for data storage has long been on-premises; however, with advances in cloud technologies, new alternatives have emerged that are more efficient, secure, and affordable. As organizations realize the benefits of cloud computing, conventional storage methods are gradually being replaced by cloud computing. It is expected that digital transformation will result in an increase in the number of enterprises migrating their data management systems to the cloud over the next few years.

The transition to this new technology does not only result from technological developments, but it is also a strategic necessity to remain competitive in a rapidly evolving environment of business. In today's fast-paced business environment, data has become one of the most crucial assets for decision-making, operational efficiency, and innovation, which emphasizes the need for organizations to implement robust and scalable strategies for managing data.

With the continued evolution of industries, it is increasingly important that organizations ensure that they have a well-structured and efficient data management framework to ensure long-term success. As the data-driven world becomes increasingly data-driven, these companies will be better able to adapt to market shifts, enhance their overall business agility, and leverage real-time analytics through the use of cloud-based technology solutions, enhancing their competitiveness in the increasingly data-driven world.

AI Technology is Helping Criminal Groups Grow Stronger in Europe, Europol Warns

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AI Technology is Helping Criminal Groups Grow Stronger in Europe, Europol Warns

The European Union’s main police agency, Europol, has raised an alarm about how artificial intelligence (AI) is now being misused by criminal groups. According to their latest report, criminals are using AI to carry out serious crimes like drug dealing, human trafficking, online scams, money laundering, and cyberattacks.

This report is based on information gathered from police forces across all 27 European Union countries. Released every four years, it helps guide how the EU tackles organized crime. Europol’s chief, Catherine De Bolle, said cybercrime is growing more dangerous as criminals use advanced digital tools. She explained that AI is giving criminals more power, allowing them to launch precise and damaging attacks on people, companies, and even governments.

Some crimes, she noted, are not just about making money. In certain cases, these actions are also designed to cause unrest and weaken countries. The report explains that criminal groups are now working closely with some governments to secretly carry out harmful activities.

One growing concern is the rise in harmful online content, especially material involving children. AI is making it harder to track and identify those responsible because fake images and videos look very real. This is making the job of investigators much more challenging.

The report also highlights how criminals are now able to trick people using technology like voice imitation and deepfake videos. These tools allow scammers to pretend to be someone else, steal identities, and threaten people. Such methods make fraud, blackmail, and online theft harder to spot.

Another serious issue is that countries are now using criminal networks to launch cyberattacks against their rivals. Europol noted that many of these attacks are aimed at important services like hospitals or government departments. For example, a hospital in Poland was recently hit by a cyberattack that forced it to shut down for several hours. Officials said the use of AI made this attack more severe.

The report warns that new technology is speeding up illegal activities. Criminals can now carry out their plans faster, reach more people, and operate in more complex ways. Europol urged countries to act quickly to tackle this growing threat.

The European Commission is planning to introduce a new security policy soon. Magnus Brunner, the EU official in charge of internal affairs, said Europe needs to stay alert and improve safety measures. He also promised that Europol will get more staff and better resources in the coming years to fight these threats.

In the end, the report makes it clear that AI is making crime more dangerous and harder to stop. Stronger cooperation between countries and better cyber defenses will be necessary to protect people and maintain safety across Europe.

Over Half of Organizations Lack AI Cybersecurity Strategies, Mimecast Report Reveals

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Over Half of Organizations Lack AI Cybersecurity Strategies, Mimecast Report Reveals

More than 55% of organizations have yet to implement dedicated strategies to counter AI-driven cyber threats, according to new research by Mimecast. The cybersecurity firm's latest State of Human Risk report, based on insights from 1,100 IT security professionals worldwide, highlights growing concerns over AI vulnerabilities, insider threats, and cybersecurity funding shortfalls.

The study reveals that 96% of organizations report improved risk management after adopting a formal cybersecurity strategy. However, security leaders face an increasingly complex threat landscape, with AI-powered attacks and insider risks posing significant challenges.

“Despite the complexity of challenges facing organisations—including increased insider risk, larger attack surfaces from collaboration tools, and sophisticated AI attacks—organisations are still too eager to simply throw point solutions at the problem,” said Mimecast’s human risk strategist VP, Masha Sedova. “With short-staffed IT and security teams and an unrelenting threat landscape, organisations must shift to a human-centric platform approach that connects the dots between employees and technology to keep the business secure.”

The report finds that 95% of organizations are leveraging AI for threat detection, endpoint security, and insider risk analysis. However, 81% express concerns over data leaks from generative AI (GenAI) tools. More than half lack structured strategies to combat AI-driven attacks, while 46% remain uncertain about their ability to defend against AI-powered phishing and deepfake threats.

Insider threats have surged by 43%, with 66% of IT leaders anticipating an increase in data loss from internal sources in the coming year. The report estimates that insider-driven data breaches, leaks, or theft cost an average of $13.9 million per incident. Additionally, 79% of organizations believe collaboration tools have heightened security risks, amplifying both intentional and accidental data breaches.

Despite 85% of organizations raising their cybersecurity budgets, 61% cite financial constraints as a barrier to addressing emerging threats and implementing AI-driven security solutions. The report underscores the need for increased investment in cybersecurity staffing, third-party security services, email security, and collaboration tool protection.

Although 87% of organizations conduct quarterly cybersecurity training, 33% of IT leaders remain concerned about employee mismanagement of email threats, while 27% cite security fatigue as a growing risk. 95% of organizations expect email-based cyber threats to persist in 2025, as phishing attacks continue to exploit human vulnerabilities.

Collaboration tools are expanding attack surfaces, with 44% of organizations reporting a rise in cyber threats originating from these platforms. 61% believe a cyberattack involving collaboration tools could disrupt business operations in 2025, raising concerns over data integrity and compliance.

The report highlights a shift from traditional security awareness training to proactive Human Risk Management. Notably, just 8% of employees are responsible for 80% of security incidents. Organizations are increasingly turning to AI-driven monitoring and behavioral analytics to detect and mitigate threats early. 72% of security leaders see human-centric cybersecurity solutions as essential in the next five years, signaling a shift toward advanced threat detection and risk mitigation.

Hawcx Aims to Solve Passkey Challenges with Passwordless Authentication

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Hawcx Aims to Solve Passkey Challenges with Passwordless Authentication

Passwords remain a staple of online security, despite their vulnerabilities. According to Verizon, nearly one-third of all reported data breaches in the past decade resulted from stolen credentials, including some of the largest cyberattacks in history.

In response, the tech industry has championed passkeys as a superior alternative to passwords. Over 15 billion accounts now support passkey technology, with major companies such as Amazon, Apple, Google, and Microsoft driving adoption.

However, widespread adoption remains sluggish due to concerns about portability and usability. Many users find passkeys cumbersome, particularly when managing access across multiple devices.

Cybersecurity startup Hawcx is addressing these passkey limitations with its innovative authentication technology. By eliminating key storage and transmission issues, Hawcx enhances security while improving usability.

Users often struggle with passkey setup and access across devices, leading to account lockouts and costly recovery—a significant challenge for businesses. As Dan Goodin of Ars Technica highlights, while passkeys offer enhanced security, their complexity can introduce operational inefficiencies at scale.

Hawcx, founded in 2023 by Riya Shanmugam (formerly of Adobe, Google, and New Relic), along with Selva Kumaraswamy and Ravi Ramaraju, offers a platform-agnostic solution. Developers can integrate its passwordless authentication by adding just five lines of code.

Unlike traditional passkeys, Hawcx does not store or transmit private keys. Instead, it cryptographically generates private keys each time a user logs in. This method ensures compatibility with older devices that lack modern hardware for passkey support.

“We are not reinventing the wheel fundamentally in most of the processes we have built,” Shanmugam told TechCrunch.

If a user switches devices, Hawcx’s system verifies authenticity before granting access, without storing additional private keys on the new device or in the cloud. This approach differs from standard passkeys, which require syncing private keys across devices or through cloud services.

“No one is challenging beyond the foundation,” Shanmugam said. “What we are challenging is the foundation itself. We are not building on top of what passkeys as a protocol provides. We are saying this protocol comes with an insane amount of limitations for users, enterprises, and developers, and we can make it better.”

Although Hawcx has filed patents, its technology has yet to be widely deployed or independently validated—factors that could influence industry trust. However, the company recently secured $3 million in pre-seed funding from Engineering Capital and Boldcap to accelerate development and market entry.

Shanmugam revealed that Hawcx is in talks with major banks and gaming companies for pilot programs set to launch in the coming weeks. These trials, expected to run for three to six months, will help refine the technology before broader implementation. Additionally, the startup is working with cryptography experts from Stanford University to validate its approach.

“As we are rolling out passkeys, the adoption is low. It’s clear to me that as good as passkeys are and they have solved the security problem, the usability problem still remains,” Tushar Phondge, director of consumer identity at ADP, told TechCrunch.

ADP plans to pilot Hawcx’s solution to assess its effectiveness in addressing passkey-related challenges, such as device dependency and system lockups.

Looking ahead, Hawcx aims to expand its authentication platform by integrating additional security services, including document verification, live video authentication, and background checks.

Microsoft and Amazon’s Quantum Progress Poses New Risks for Encryption

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Microsoft and Amazon’s Quantum Progress Poses New Risks for Encryption

Microsoft, Amazon, and Google have all announced recent advances in quantum computing that are likely to accelerate the timeline for the possible obsolescence of current encryption standards. These developments indicate that it will become increasingly important to address the vulnerabilities posed by quantum computing to existing cryptographic protocols shortly. Those who are leading the way in the technological race are those who are advancing quantum computing technology, which is the most powerful technology that will be able to easily decrypt the encryption mechanisms that safeguard the internet's security and data privacy.

On the other hand, there are researchers and cybersecurity experts who are working on the development of post-quantum cryptography (PQC) - a new generation of encryption technologies that can handle quantum system computational power with ease. A quantum-resistant encryption system must be prioritized by organisations and governments to ensure long-term security of their data and digital communications, especially as the quantum era has come closer than anticipated to being realized.

Even though quantum decryption and quantum-resistant encryption are competing more than ever, the race for global cybersecurity infrastructure requires strategic investment and proactive measures. There has been an important advancement in quantum computing in the field, with Amazon Web Services (AWS) announcing the inaugural quantum computing chip called Ocelot, which represents a significant step in the pursuit of practical quantum computing.

One of the most critical challenges in the field is error correction. Using Ocelot, Amazon Web Services claims that it may be possible to drastically reduce the cost of quantum error correction by as much as 90 percent, thus speeding up the process toward fault-tolerant quantum systems being realized. In the future, error correction will continue to be an important barrier to quantum computing. This is because quantum systems are inherently fragile, as well as highly susceptible to environmental disturbances, such as fluctuating temperatures, electromagnetic interference, and vibrations from the environment.

As a result of these external factors, quantum operations are exposed to a substantial amount of computational errors, which make it extremely challenging to maintain their stability and reliability. Research in quantum computing is progressing rapidly, which means innovations like Ocelot could play a crucial role in helping mitigate these challenges, paving the way for more robust and scalable quantum computing in the future.

If a sufficiently advanced quantum computer has access to Shor's algorithm or any potential enhancements to it, it will be possible for it to decrypt existing public key encryption protocols, such as RSA 2048, within 24 hours by leveraging Shor's algorithm. With the advent of quantum computing, modern cybersecurity frameworks are going to be fundamentally disrupted, rendering current cryptographic mechanisms ineffective.

The encryption of any encrypted data that has been unauthorizedly acquired and stored under the "harvest now, decrypt later" strategy will become fully available to those who have such quantum computing capabilities. A severe breach of internet communications, digital signatures, and financial transactions would result in severe breaches of trust in the digital ecosystem, resulting in serious losses in trust. The inevitability of this threat does not depend on the specific way by which PKE is broken, but rather on the certainty that a quantum system with sufficient power will be able to achieve this result in the first place.

Consequently, the National Institute of Standards and Technology (NIST) has been the frontrunner in developing advanced encryption protocols designed to withstand quantum-based attacks in response to these threats. Post-quantum cryptography (PQC) is an initiative that is based on mathematical structures that are believed to be immune from quantum computational attacks, and is a product of this effort. To ensure the long-term security of digital infrastructure, PKE must be replaced with PQC. There is, however, still a limited amount of awareness of the urgency of the situation, and many stakeholders are still unaware of quantum computing's potential impact on cybersecurity, and are therefore unaware of its potential.

As the development of quantum-resistant encryption technologies through 2025 becomes increasingly important, it will play an increasingly important role in improving our understanding of these methodologies, accelerating their adoption, and making sure our global cybersecurity standards will remain safe. For a cryptographic method to be effective, it must have computationally infeasible algorithms that cannot be broken within a reasonable period. These methods allow for secure encryption and decryption, which ensures that data is kept confidential for authorized parties. However, no encryption is completely impervious indefinitely.

A sufficiently powerful computing machine will eventually compromise any encryption protocol. Because of this reality, cryptographic standards have continuously evolved over the past three decades, as advances in computing have rendered many previous encryption methods obsolete. For example, in the "crypto wars" of the 1990s, the 1024-bit key encryption that was at the center of the debate has long been retired and is no longer deemed adequate due to modern computational power. Nowadays, it is hardly difficult for a computer to break through that level of encryption.

In recent years, major technology companies have announced that the ability to break encryption is poised to take a leap forward that has never been seen before. Amazon Web Services, Google, and Microsoft have announced dramatic increases in computational power facilitated by quantum computing technology. Google introduced "Willow" in December and Microsoft announced "Majorana 1" in February, which signals a dramatic rise in computational power. A few days later, Amazon announced the "Ocelot" quantum computing machine. Each of these breakthroughs represents an important and distinct step forward in the evolution of quantum computing technology, a technology that has fundamentally redefined the way that processors are designed.

In contrast to traditional computing systems, quantum systems are based on entirely different principles, so their efficiency is exponentially higher. It is evident that advances in quantum computing are accelerating an era that will have a profound effect on encryption security and that cybersecurity practices need to be adjusted urgently to cope with these advances. In recent years, quantum computing has made tremendous strides in computing power. It has led to an extraordinary leap in computational power unmatched by any other technology. In the same manner as with any technological breakthrough that has an impact on our world, it is uncertain what it may mean.

However, there is one aspect that is becoming increasingly clear: the computational barriers that define what is currently infeasible will be reduced to problems that can be solved in seconds, as stated by statements from Google and Microsoft. In terms of data security, this change has profound implications. It will be very easy for quantum computers to unlock encrypted information once they become widely accessible, thus making it difficult to decrypt encrypted data today. Having the capability to break modern encryption protocols within a matter of seconds poses a serious threat to digital privacy and security across industries.

The development of quantum-resistant cryptographic solutions has been undertaken in anticipation of this eventuality. A key aspect of the Post-Quantum Cryptography (PQC) initiative has been the leadership role that NIST has been assuming since 2016, as it has played a historical role in establishing encryption standards over the years. NIST released a key milestone in global cybersecurity efforts in August when it released its first three finalized post-quantum encryption standards.

Major technology companies, including Microsoft, Amazon Web Services (AWS), and Google, are not only contributing to the advancement of quantum computing but are also actively participating in the development of PQC solutions as well. Google has been working with NIST on developing encryption methods that can withstand quantum-based attacks. These organizations have been working together with NIST to develop encryption methods that can withstand quantum attacks. During August, Microsoft provided an update on their PQC efforts, followed by AWS and Microsoft.

The initiatives have been in place long before the latest quantum hardware advances, yet they are a strong reminder that addressing the challenges posed by quantum computing requires a comprehensive and sustained commitment. However, establishing encryption standards does not guarantee widespread adoption, as it does not equate to widespread deployment. As part of the transition, there will be a considerable amount of time and effort involved, particularly in ensuring that it integrates smoothly into everyday applications, such as online banking and secure communications, thereby making the process more complex and time consuming.

Because of the challenges associated with implementing and deploying new encryption technologies on a large scale, the adoption of new encryption technologies has historically spanned several years. Due to this fact, it cannot be overemphasized how urgent it is for us to prepare for a quantum era. A company's strategic planning and system design must take into account PQC considerations proactively and proactively. It has become increasingly clear that all organizations must address the issue of PQC rather than delay it. The fundamental principle remains that if the user breaks encryption, they are much more likely to break it than if they construct secure systems.

Moreover, cryptographic implementation is a complex and error-prone process in and of itself. For the cybersecurity landscape to be successful at defending against quantum-based threats, a concerted, sustained effort must be made across all aspects. There is a lot of excitement on the horizon for encryption, both rapidly and very challenging. As quantum computing emerges, current encryption protocols face an existential threat, which means that organizations that fail to react quickly and decisively will suffer severe security vulnerabilities, so ensuring the future of digital security is imperative.

Seattle Startup Develops AI to Automate Office Work

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Technology

Artificial Intelligence Caddi Seattle Technology

Seattle Startup Develops AI to Automate Office Work

A new startup in Seattle is working on artificial intelligence (AI) that can take over repetitive office tasks. The company, called Caddi, has recently secured $5 million in funding to expand its technology. Its goal is to reduce manual work in businesses by allowing AI to learn from human actions and create automated workflows.

Caddi was founded by Alejandro Castellano and Aditya Sastry, who aim to simplify everyday office processes, particularly in legal and financial sectors. Instead of requiring employees to do routine administrative work, Caddi’s system records user activity and converts it into automated processes.

How Caddi’s AI Works

Caddi’s approach is based on a method known as “automation by demonstration.” Employees perform a task while the system records their screen and listens to their explanation. The AI then studies these recordings and creates an automated system that can carry out the same tasks without human input.

Unlike traditional automation tools, which often require technical expertise to set up, Caddi’s technology allows anyone to create automated processes without needing programming knowledge. This makes automation more accessible to businesses that may not have in-house IT teams.

Founders and Background

Caddi was launched in August by Alejandro Castellano and Aditya Sastry. Castellano, originally from Peru, has experience managing financial investments and later pursued a master’s degree in engineering at Cornell University. Afterward, he joined an AI startup incubator, where he focused on developing new technology solutions.

Sastry, on the other hand, has a background in data science and has led engineering teams at multiple startups. Before co-founding Caddi, he was the director of engineering at an insurance technology firm. The founding team also includes Dallas Slaughter, an experienced engineer.

The company plans to grow its team to 15 employees over the next year. Investors supporting Caddi include Ubiquity Ventures, Founders’ Co-op, and AI2 Incubator. As part of the investment deal, Sunil Nagaraj, a general partner at Ubiquity Ventures, has joined Caddi’s board. He has previously invested in successful startups, including a company that was later acquired for billions of dollars.

Competing with Other Automation Tools

AI-powered automation is a growing industry, and Caddi faces competition from several other companies. Platforms like Zapier and Make also offer automation services, but they require users to understand concepts like data triggers and workflow mapping. In contrast, Caddi eliminates the need for manual setup by allowing AI to learn directly from user actions.

Other competitors, such as UiPath and Automation Anywhere, rely on mimicking human interactions with software, such as clicking buttons and filling out forms. However, this method can be unreliable when software interfaces change. Caddi takes a different approach by connecting directly with software through APIs, making its automation process more stable and accurate.

Future Plans and Industry Impact

Caddi began testing its AI tools with a small group of users in late 2024. The company is now expanding access and plans to release its automation tools to the public as a subscription service later this year.

As businesses look for ways to improve efficiency and reduce costs, AI-powered automation is becoming increasingly popular. However, concerns remain about the reliability and accuracy of these tools, especially in highly regulated industries. Caddi aims to address these concerns by offering a system that minimizes errors and is easier to use than traditional automation solutions.

By allowing professionals in law, finance, and other fields to automate routine tasks, Caddi’s technology helps businesses focus on more important work. Its approach to AI-driven automation could change how companies handle office tasks, making work faster and more efficient.

Webcam Exploited by Ransomware Group to Circumvent EDR Protections

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Windows

Akira CyberCrime Cybersecurity Cyberthreats EDR EDR Protections Ransomware S-RM Technology Webcam Windows

Webcam Exploited by Ransomware Group to Circumvent EDR Protections

Researchers at S-RM have discovered an unusual attack method used by the Akira ransomware gang. The Akira ransomware gang utilized an unsecured webcam to conduct encryption attacks against victims' networks via the use of an unsecured webcam. The attackers were able to bypass the Endpoint Detection and Response (EDR) mechanisms, which had been successful in stopping the ransomware encryptor from functioning on Windows computers.

During an investigation conducted by the S-RM team as part of an incident response, the S-RM team uncovered Akira's sophisticated adaptations in response to security defences. As a first step, the threat actors tried to implement encryption tools on Windows endpoints, but these attempts were thwarted by the EDR solution provided by the victim.

It is important to note that the attackers reacted to this by exploiting the unsecured webcam as an entry point for the malware to infiltrate the network and launch their ransomware attacks. This incident illustrates how ransomware operators are increasingly using unconventional vulnerabilities to circumvent modern cybersecurity defenses, highlighting the evolution of ransomware operations.

Network vulnerabilities exploited by Akira ransomware operators.

Researchers in the cybersecurity field recently discovered a sophisticated attack strategy that was employed by the Akira ransomware group. Initially, the threat actors gained access to the network via an externally exposed remote access solution through which unauthorized access was gained. The attackers then installed AnyDesk.exe, a legitimate remote desktop tool, to maintain persistent access within the compromised network, and proceeded to exfiltrate sensitive data using this tool.

In the months following the initial breach, the attackers used Remote Desktop Protocol (RDP) to move laterally through the network, simulating legitimate system administrator activities to conceal their activity and blend into normal networking operations. They evaded detection by mimicking legitimate system administrator activities.

Akira Ransomware Group: A Rising Threat in the Cybercrime Landscape

Emergence and Rapid Expansion

Originally identified in early 2023, the Akira ransomware group has rapidly gained popularity as one of the most active ransomware operations in the world. As of 2024, the Akira group is responsible for around 15% of all ransomware incidents that were examined by cybersecurity firm S-RM. The company specializes in targeting small to medium sized businesses (SMEs) in North America, Europe, and Australia, especially businesses that have fewer than 1,000 employees as their primary target market.

Operational Model and Organizational Structure

Rather than using the typical paid-for model, Akira also uses a ransomware-as-a-service model: within this model, the group's core developers provide a running platform that allows its affiliates to access its binary and leak sites in exchange for a share of the ransom payments received by the group's owners.

Triple Extortion Strategy and Technical Adaptability

By employing a triple approach of extortion, or a series of layers of coercion to maximize leverage over their victims, Akira achieves extreme leverage over them:

Data Encryption – Locking files and systems to disrupt business operations.

Data Exfiltration – Stealing sensitive information before encryption.

Public Disclosure Threats – Threatening to release exfiltrated data unless the ransom is paid.

Akira's technical adaptability is exemplified by its ability to adjust its attack methods based on security threats. A recent webcam attack highlighted the group's innovative tactics. In this case, the group circumvented Endpoint Detection and Response (EDR) protections by using unsecured Internet of Things devices as an alternative entry point to bypass the system's protections.

As ransomware operations such as Akira become more sophisticated, organizations, particularly small and medium-sized enterprises, must take proactive cybersecurity measures to mitigate the threats posed by these highly adaptive threat actors. To mitigate these risks, organizations must implement robust endpoint security, network segmentation, and IoT security protocols.

Initially, the threat actors managed to breach the corporate network through an exposed remote access solution, likely using stolen credentials or brute-force techniques to gain access to the network. Once inside, they deployed AnyDesk, an authentic remote access tool, to gain persistent access and gain access to sensitive data. The data was then used as leverage in a double extortion scheme that later resulted in a double extortion attack.

When the attack was first initiated, the attackers took advantage of the Remote Desktop Protocol (RDP) to enable them to move laterally, systematically spreading their presence across multiple systems before launching the ransomware attack. Their attack was carried out by introducing a password-protected archive file, win.zip, with the ransomware payload, win.exe, as a payload. Although the threat was initially detected and quarantined by the victim's Endpoint Detection and Response (EDR) system, it was ultimately neutralized when the virus was identified and quarantined.

The attackers modified their strategy after experiencing this setback by finding alternative ways to attack the device. During a thorough network scan, several potential entry points were discovered, including a webcam and a fingerprint scanner. S-RM, a cybersecurity firm, explains that threat actors eventually chose the webcam as their primary pivot point for gaining access to its data, as it is easy for remote shell access and unauthorized video feeds. Moreover, the attackers took advantage of the device's lightweight Linux-based operating system, which was compatible with Akira's Linux encryptor.

Since the webcam was without a protection agent against EDR attacks, it was an ideal choice for the ransomware attack to take place. The threat actors were able to successfully encrypt files on network shares by leveraging their connectivity to the Internet, circumventing conventional security measures and demonstrating the evolving sophistication of ransomware tactics. Instead of abandoning their original objective, the ransomware operators chose to utilize a previous internal network scan data as the basis for their next strategy.

An investigation of the Internet of Things (IoT) revealed that several vulnerable devices were not adequately protected, including webcams and fingerprint scanners. As the attackers recognized the potential of unprotected devices as alternative entry points to traditional security systems, they sought to bypass those mechanisms. They discovered several vulnerabilities during their assessment, including an unsecured webcam, which proved to be the most feasible vulnerability.

Several reasons contributed to this, most notably that it lacked Endpoint Detection and Response (EDR) protection, which made it an ideal target for exploiting. Additionally, the device was capable of being accessed remotely through a remote shell, making it even easier for attackers to gain access.

In addition, the Linux-based operating system presented a lightweight security footprint, which reduced the chances of detection and strengthened the appeal of the operating system as a potential entry point for cybercriminals. Execution of the Attack Through IoT Exploitation This attacker was able to create malicious SMB traffic directed towards a target Windows server by compromising a vulnerable webcam, which was able to be used by the attacker to create malicious SMB traffic.

Due to the organization's lack of active monitoring of IoT devices, this technique enabled the ransomware payload to bypass traditional detection mechanisms. As a result of the attack, a large number of files were encrypted across the network of the victim. Even though SMB-based attacks have generally been considered to be less efficient than other intrusion techniques, this attack proved extremely effective in this case, mainly because they are frequently incompatible with conventional security monitoring tools, such as this tool.

It is as a consequence of this incident that organizations must take proactive steps to ensure that all network-connected devices, most notably IoT endpoints, are secured via encryption so that sophisticated ransomware operators are not able to exploit them as attack vectors.

The fact that the compromised webcam lacked an Endpoint Detection and Response (EDR) protection was a critical factor in the success of this attack, as largely due to its limited storage capacity, it could not cope with advanced security measures needed to defend itself.

The Akira ransomware group exploited this vulnerability to deploy its Linux-based ransomware quickly from the compromised machine, encrypting files across the victim's network by using the Server Message Block protocol (SMB). As a result of this strategic approach, the attackers were able to operate covertly since malicious SMB traffic originating from the webcam was not detected by security systems, allowing them to evade detection by the organization's cybersecurity team.

In light of these events, it is due to the growing necessity for comprehensive security protocols, in particular for securing Internet of Things (IoT) devices, that are more and more exploited as attack vectors by cyber criminals. A proactive cybersecurity approach is imperative to mitigate similar threats by ensuring that IoT devices are patched and managed, conducting regular vulnerability assessments within the organization's internal networks, and implementing robust network segmentation so that connected devices are limited in their ability to communicate.

Further, turning off IoT devices when not in use can serve as a preventive measure against potential exploitation. To effectively defend against emerging threats, it is imperative to continuously monitor your network and implement robust security frameworks. As demonstrated by the Akira ransomware group, you must monitor your network constantly and implement robust security measures. With ransomware-as-a-service (RaaS) operations continuing to evolve at a rapid pace, organizations must remain vigilant, improving their cybersecurity strategies proactively to remain protected from increasingly sophisticated cyberattacks.

Quantum Computers Threaten to Breach Online Security in Minutes

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Threat Intelligence

Online Security Quantum Computers Security Breach Technology Threat Intelligence

Quantum Computers Threaten to Breach Online Security in Minutes

A perfect quantum computer could decrypt RSA-2048, our current strongest encryption, in 10 seconds. Quantum computing employs the principle of quantum physics to process information using quantum bits (qubits) rather than standard computer bits. Qubits can represent both states at the same time, unlike traditional computers, which employ bits that are either 0 or 1. This capacity makes quantum computers extremely effective in solving complicated problems, particularly in cryptography, artificial intelligence, and materials research.

While this computational leap opens up incredible opportunities across businesses, it also raises serious security concerns. When quantum computers achieve their full capacity, they will be able to break through standard encryption methods used to safeguard our most sensitive data. While the timescale for commercial availability of fully working quantum computers is still uncertain, projections vary widely.

The Boston Consulting Group predicts a significant quantum advantage between 2030 and 2040, although Gartner believes that developments in quantum computing could begin to undermine present encryption approaches as early as 2029, with complete vulnerability by 2034. Regardless of the precise timetable, the conclusion is unanimous: the era of quantum computing is quickly approaching.

Building quantum resilience

To address this impending threat, organisations must:

Adopt new cryptographic algorithms that are resistant against impending quantum attacks, such as post-quantum cryptography (PQC). The National Institute of Standards and Technology (NIST) recently published its first set of PQC algorithm standards (FIPS 203, FIPS 204, and FIPS 205) to assist organisations in safeguarding their data from quantum attacks.
Upgrades will be required across the infrastructure. Develop crypto agility to adapt to new cryptographic methods without requiring massive system overhauls as threats continue to evolve.

This requires four essential steps:

Discover and assess: Map out where your organisation utilises cryptography and evaluate the quantum threats to its assets. Identify the crown jewels and potential business consequences.

Strategise: Determine the current cryptography inventory, asset lives against quantum threat timelines, quantum risk levels for essential business assets, and create an extensive PQC migration path.

Modernise: Implement quantum-resilient algorithms while remaining consistent with overall company strategy.

Enhance: Maintain crypto agility by providing regular updates, asset assessments, modular procedures, continual education, and compliance monitoring.

The urgency to act

In the past, cryptographic migrations often took more than ten years to finish. Quantum-resistant encryption early adopters have noticed wide-ranging effects, such as interoperability issues, infrastructure rewrites, and other upgrading challenges, which have resulted in multi-year modernisation program delays.

The lengthy implementation period makes getting started immediately crucial, even though the shift to PQC may be a practical challenge given its extensive and dispersed distribution throughout the digital infrastructure. Prioritising crypto agility will help organisations safeguard critical details before quantum threats materialise.

AI as a Key Solution for Mitigating API Cybersecurity Threats

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Technology

AI AI vulnerabilities API Artificial Intelligence CERT-In CyberCrime Cyberhackers CyberThreat Technology

AI as a Key Solution for Mitigating API Cybersecurity Threats

Artificial Intelligence (AI) is continuously evolving, and it is fundamentally changing the cybersecurity landscape, enabling organizations to mitigate vulnerabilities more effectively as a result. As artificial intelligence has improved the speed and scale with which threats can be detected and responded, it has also introduced a range of complexities that necessitate a hybrid approach to security management.

An approach that combines traditional security frameworks with human-digital interventions is necessary. There is one of the biggest challenges AI presents to us, and that is the expansion of the attack surface for Application Programming Interfaces (APIs). The proliferation of AI-powered systems raises questions regarding API resilience as sophisticated threats become increasingly sophisticated. As AI-driven functionality is integrated into APIs, security concerns have increased, which has led to the need for robust defensive strategies.

In the context of AI security, the implications of the technology extend beyond APIs to the very foundation of Machine Learning (ML) applications as well as large language models. Many of these models are trained on highly sensitive datasets, raising concerns about their privacy, integrity, and potential exploitation. When training data is handled improperly, unauthorized access can occur, data poisoning can occur, and model manipulation may occur, which can further increase the security vulnerability.

It is important to note, however, that artificial intelligence is also leading security teams to refine their threat modeling strategies while simultaneously posing security challenges. Using AI's analytical capabilities, organizations can enhance their predictive capabilities, automate risk assessments, and implement smarter security frameworks that can be adapted to the changing environment. By adapting to this evolution, security professionals are forced to adopt a proactive and adaptive approach to reducing potential threats.

Using artificial intelligence effectively while safeguarding digital assets requires an integrated approach that combines traditional security mechanisms with AI-driven security solutions. This is necessary to ensure an effective synergy between automation and human oversight. Enterprises must foster a comprehensive security posture that integrates both legacy and emerging technologies to be more resilient in the face of a changing threat landscape. However, the deployment of AI in cybersecurity requires a well-organized, strategic approach. While AI is an excellent tool for cybersecurity, it does need to be embraced in a strategic and well-organized manner.

Building a robust and adaptive cybersecurity ecosystem requires addressing API vulnerabilities, strengthening training data security, and refining threat modeling practices. A major part of modern digital applications is APIs, allowing seamless data exchange between various systems, enabling seamless data exchange. However, the widespread adoption of APIs has also led to them becoming prime targets for cyber threats, which have put organizations at risk of significant risks, such as data breaches, financial losses, and disruptions in services.

AI platforms and tools, such as OpenAI, Google's DeepMind, and IBM's Watson, have significantly contributed to advancements in several technological fields over the years. These innovations have revolutionized natural language processing, machine learning, and autonomous systems, leading to a wide range of applications in critical areas such as healthcare, finance, and business. Consequently, organizations worldwide are turning to artificial intelligence to maximize operational efficiency, simplify processes, and unlock new growth opportunities.

While artificial intelligence is catalyzing progress, it also introduces potential security risks. In addition to manipulating the very technologies that enable industries to orchestrate sophisticated cyber threats, cybercriminals can also use those very technologies. As a result, AI is viewed as having two characteristics: while it is possible for AI-driven security systems to proactively identify, predict, and mitigate threats with extraordinary accuracy, adversaries can weaponize such technologies to create highly advanced cyberattacks, such as phishing schemes and ransomware.

It is important to keep in mind that, as AI continues to grow, its role in cybersecurity is becoming more complex and dynamic. Organizations need to take proactive measures to protect their organizations from AI attacks by implementing robust frameworks that harness its defensive capabilities and mitigate its vulnerabilities. For a secure digital ecosystem that fosters innovation without compromising cybersecurity, it will be crucial for AI technologies to be developed ethically and responsibly.

The Application Programming Interface (API) is the fundamental component of digital ecosystems in the 21st century, enabling seamless interactions across industries such as mobile banking, e-commerce, and enterprise solutions. They are also a prime target for cyber-attackers due to their widespread adoption. The consequences of successful breaches can include data compromises, financial losses, and operational disruptions that can pose significant challenges to businesses as well as consumers alike.

Pratik Shah, F5 Networks' Managing Director for India and SAARC, highlighted that APIs are an integral part of today's digital landscape. AIM reports that APIs account for nearly 90% of worldwide web traffic and that the number of public APIs has grown 460% over the past decade. Despite this rapid proliferation, the company has been exposed to a wide array of cyber risks, including broken authentication, injection attacks, and server-side request forgery. According to him, the robustness of Indian API infrastructure significantly influences India's ambitions to become a global leader in the digital industry.

“APIs are the backbone of our digital economy, interconnecting key sectors such as finance, healthcare, e-commerce, and government services,” Shah remarked. Shah claims that during the first half of 2024, the Indian Computer Emergency Response Team (CERT-In) reported a 62% increase in API-targeted attacks. The extent of these incidents goes beyond technical breaches, and they represent substantial economic risks that threaten data integrity, business continuity, and consumer trust in addition to technological breaches.

Aside from compromising sensitive information, these incidents have also undermined business continuity and undermined consumer confidence, in addition to compromising business continuity. APIs will continue to be at the heart of digital transformation, and for that reason, ensuring robust security measures will be critical to mitigating potential threats and protecting organisational integrity.

Indusface recently published an article on API security that underscores the seriousness of API-related threats for the next 20 years. There has been an increase of 68% in attacks on APIs compared to traditional websites in the report. Furthermore, there has been a 94% increase in Distributed Denial-of-Service (DDoS) attacks on APIs compared with the previous quarter. This represents an astounding 1,600% increase when compared with website-based DDoS attacks.

Additionally, bot-driven attacks on APIs increased by 39%, emphasizing the need to adopt robust security measures that protect these vital digital assets from threats. As a result of Artificial Intelligence, cloud security is being transformed by enhancing threat detection, automating responses, and providing predictive insights to mitigate cyber risks.

Several cloud providers, including Google Cloud, Microsoft, and Amazon Web Services, employ artificial intelligence-driven solutions for monitoring security events, detecting anomalies, and preventing cyberattacks.

The solutions include Chronicle, Microsoft Defender for Cloud, and Amazon GuardDuty. Although there are challenges like false positives, adversarial AI attacks, high implementation costs, and concerns about data privacy, they are still important to consider.

Although there are still some limitations, advances in self-learning AI models, security automation, and quantum computing are expected to raise AI's profile in the cybersecurity space to a higher level. The cloud environment should be safeguarded against evolving threats by using AI-powered security solutions that can be deployed by businesses.

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Hawcx Aims to Solve Passkey Challenges with Passwordless Authentication

Microsoft and Amazon’s Quantum Progress Poses New Risks for Encryption

Seattle Startup Develops AI to Automate Office Work

Webcam Exploited by Ransomware Group to Circumvent EDR Protections

Network vulnerabilities exploited by Akira ransomware operators.

Akira Ransomware Group: A Rising Threat in the Cybercrime Landscape

Emergence and Rapid Expansion

Operational Model and Organizational Structure

Triple Extortion Strategy and Technical Adaptability

Quantum Computers Threaten to Breach Online Security in Minutes

AI as a Key Solution for Mitigating API Cybersecurity Threats

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Network vulnerabilities exploited by Akira ransomware operators.

Akira Ransomware Group: A Rising Threat in the Cybercrime Landscape

Emergence and Rapid Expansion

Operational Model and Organizational Structure

Triple Extortion Strategy and Technical Adaptability