Cyberattacks are becoming alarmingly frequent, with a new attack occurring approximately every 39 seconds. These attacks, ranging from phishing schemes to ransomware, have devastating impacts on businesses worldwide. The cost of cybercrime is projected to hit $9.5 trillion in 2024, and with AI being leveraged by cybercriminals, this figure is likely to rise.
According to a recent RiverSafe report surveying Chief Information Security Officers (CISOs) in the UK, one in five CISOs identifies AI as the biggest cyber threat. The increasing availability and sophistication of AI tools are empowering cybercriminals to launch more complex and large-scale attacks. The National Cyber Security Centre (NCSC) warns that AI will significantly increase the volume and impact of cyberattacks, including ransomware, in the near future.
AI is enhancing traditional cyberattacks, making them more difficult to detect. For example, AI can modify malware to evade antivirus software. Once detected, AI can generate new variants of the malware, allowing it to persist undetected, steal data, and spread within networks. Additionally, AI can bypass firewalls by creating legitimate-looking traffic and generating convincing phishing emails and deepfakes to deceive victims into revealing sensitive information.
Policies to Mitigate AI Misuse
AI misuse is not only a threat from external cybercriminals but also from employees unknowingly putting company data at risk. One in five security leaders reported experiencing data breaches due to employees sharing company data with AI tools like ChatGPT. These tools are popular for their efficiency, but employees often do not consider the security risks when inputting sensitive information.
In 2023, ChatGPT experienced an extreme data breach, highlighting the risks associated with generative AI tools. While some companies have banned the use of such tools, this is a short-term solution. The long-term approach should focus on education and implementing carefully managed policies to balance the benefits of AI with security risks.
The Growing Threat of Insider Risks
Insider threats are a significant concern, with 75% of respondents believing they pose a greater risk than external threats. Human error, often due to ignorance or unintentional mistakes, is a leading cause of data breaches. These threats are challenging to defend against because they can originate from employees, contractors, third parties, and anyone with legitimate access to systems.
Despite the known risks, 64% of CISOs stated their organizations lack sufficient technology to protect against insider threats. The rise in digital transformation and cloud infrastructure has expanded the attack surface, making it difficult to maintain appropriate security measures. Additionally, the complexity of digital supply chains introduces new vulnerabilities, with trusted business partners responsible for up to 25% of insider threat incidents.
Preparing for AI-Driven Cyber Threats
The evolution of AI in cyber threats necessitates a revamp of cybersecurity strategies. Businesses must update their policies, best practices, and employee training to mitigate the potential damages of AI-powered attacks. With both internal and external threats on the rise, organisations need to adapt to the new age of cyber threats to protect their valuable digital assets effectively.
We are all drowning in information in this digital world and the widespread adoption of artificial intelligence (AI) has become increasingly commonplace within various spheres of business. However, this technological evolution has brought about the emergence of generative AI, presenting a myriad of cybersecurity concerns that weigh heavily on the minds of Chief Information Security Officers (CISOs). Let's synthesise this issue and see the intricacies from a microscopic light.
The lack of robust frameworks around data collection and input into generative AI models raises concerns about data privacy. Without enforceable policies, there's a risk of models inadvertently replicating and exposing sensitive corporate information, leading to data breaches.
The absence of strategic policies around generative AI and corporate data privacy can result in models being trained on proprietary codebases. This exposes valuable corporate IP, including API keys and other confidential information, to potential threats.
Despite the implementation of guardrails to prevent AI models from producing harmful or biased content, researchers have found ways to circumvent these safeguards. Known as "jailbreaks," these exploits enable attackers to manipulate AI models for malicious purposes, such as generating deceptive content or launching targeted attacks.
To mitigate these risks, organisations must adopt cybersecurity best practices tailored to generative AI usage:
1. Implement AI Governance: Establishing governance frameworks to regulate the deployment and usage of AI tools within the organisation is crucial. This includes transparency, accountability, and ongoing monitoring to ensure responsible AI practices.
2. Employee Training: Educating employees on the nuances of generative AI and the importance of data privacy is essential. Creating a culture of AI knowledge and providing continuous learning opportunities can help mitigate risks associated with misuse.
3. Data Discovery and Classification: Properly classifying data helps control access and minimise the risk of unauthorised exposure. Organisations should prioritise data discovery and classification processes to effectively manage sensitive information.
4. Utilise Data Governance and Security Tools: Employing data governance and security tools, such as Data Loss Prevention (DLP) and threat intelligence platforms, can enhance data security and enforcement of AI governance policies.
Various cybersecurity vendors provide solutions tailored to address the unique challenges associated with generative AI. Here's a closer look at some of these promising offerings:
1. Google Cloud Security AI Workbench: This solution, powered by advanced AI capabilities, assesses, summarizes, and prioritizes threat data from both proprietary and public sources. It incorporates threat intelligence from reputable sources like Google, Mandiant, and VirusTotal, offering enterprise-grade security and compliance support.
2. Microsoft Copilot for Security: Integrated with Microsoft's robust security ecosystem, Copilot leverages AI to proactively detect cyber threats, enhance threat intelligence, and automate incident response. It simplifies security operations and empowers users with step-by-step guidance, making it accessible even to junior staff members.
3. CrowdStrike Charlotte AI: Built on the Falcon platform, Charlotte AI utilizes conversational AI and natural language processing (NLP) capabilities to help security teams respond swiftly to threats. It enables users to ask questions, receive answers, and take action efficiently, reducing workload and improving overall efficiency.
4. Howso (formerly Diveplane): Howso focuses on advancing trustworthy AI by providing AI solutions that prioritize transparency, auditability, and accountability. Their Howso Engine offers exact data attribution, ensuring traceability and accountability of influence, while the Howso Synthesizer generates synthetic data that can be trusted for various use cases.
5. Cisco Security Cloud: Built on zero-trust principles, Cisco Security Cloud is an open and integrated security platform designed for multicloud environments. It integrates generative AI to enhance threat detection, streamline policy management, and simplify security operations with advanced AI analytics.
6. SecurityScorecard: SecurityScorecard offers solutions for supply chain cyber risk, external security, and risk operations, along with forward-looking threat intelligence. Their AI-driven platform provides detailed security ratings that offer actionable insights to organizations, aiding in understanding and improving their overall security posture.
7. Synthesis AI: Synthesis AI offers Synthesis Humans and Synthesis Scenarios, leveraging a combination of generative AI and cinematic digital general intelligence (DGI) pipelines. Their platform programmatically generates labelled images for machine learning models and provides realistic security simulation for cybersecurity training purposes.
These solutions represent a diverse array of offerings aimed at addressing the complex cybersecurity challenges posed by generative AI, providing organizations with the tools needed to safeguard their digital assets effectively.
While the adoption of generative AI presents immense opportunities for innovation, it also brings forth significant cybersecurity challenges. By implementing robust governance frameworks, educating employees, and leveraging advanced security solutions, organisations can navigate these risks and harness the transformative power of AI responsibly.
As businesses embrace the cloud, software-as-a-service (SaaS), and remote work, a million-dollar question arises: How will these roles evolve? The answer seems as complex as the myriad factors influencing it – company size, industry, culture, existing organizational charts, and future digital transformation plans, to name a few. Some advocate maintaining the status quo, while others propose a more specialized split between a business-oriented executive focused on risk management and compliance, and a technical executive honing in on threat prevention and response.
Regardless of the path chosen, the crux of the matter remains – the imperative need for collaboration and alignment between CIOs and CISOs. In a world where successful digital transformation is contingent upon the delicate relation between innovation and security, these IT leaders find themselves at the forefront, shaping the future of businesses large and small. The article will delve into the intricacies of this new development, shedding light on the collaborative journey of CIOs and CISOs as they navigate the ever-changing currents of technology and cybersecurity.
About two decades ago, CIOs primarily focused on managing an organization's IT infrastructure and applications. However, with the rise of digital transformation, cloud computing, and remote work, their role has shifted. Today, CIOs act as brokers of IT services, concentrating on how technology can drive innovation and effectively managing resources.
Concurrently, the profile of CISOs has been on the rise, fueled by compliance mandates, data breaches, and emerging cybersecurity threats. Compliance requirements such as HIPAA, PCI DSS, GDPR, and SOC 2 have played a dual role – increasing the visibility and budgets for cybersecurity teams but often falling short in addressing sophisticated threats like phishing and ransomware.
The growing importance of digital security at the board level has prompted CIOs, traditionally the voice of digital matters, to delve deeper into understanding cybersecurity. This trend blurs the lines between the roles of CIOs and CISOs.
Enter digital transformation, offering an opportunity to enhance cybersecurity. Despite some skepticism about its promises, digital transformation has necessitated closer collaboration between CIOs and CISOs. While CIOs continue to guide the ship, CISOs have become proactive partners, deeply involved in operational decision-making from the outset.
As companies embrace the cloud, software-as-a-service (SaaS), and remote work, the question arises – how will these roles evolve? The answer is not straightforward and depends on various factors like company size, industry, culture, and existing IT setup. Some suggest maintaining the status quo, while others propose splitting the roles into a business-oriented executive focusing on risk management and compliance, and a more technical executive concentrating on threat prevention and response.
Regardless of the direction these roles take, the overarching theme is the critical need for collaboration and alignment between CIOs and CISOs for successful digital transformation. This synergy is essential not only during the transformation process but also for navigating the evolving cybersecurity landscape.
In essence, the traditional boundaries between CIOs and CISOs are fading, giving way to a collaborative approach that acknowledges the intertwined nature of technology and cybersecurity. As companies navigate this evolution, the success of their digital transformation hinges on the ability of these IT leaders to work hand-in-hand, ensuring a secure and innovative future for businesses of all sizes.
This transformative shift emphasises the importance of simplifying and strengthening the relationship between CIOs and CISOs, creating a united front against the ever-growing challenges of the digital age.
To provide insight into the challenges faced by CISOs following a breach, cybersecurity firm Trellix surveyed over 500 security executives globally, revealing strategic analysis, eye-opening data, and practical viewpoints.
In their analysis, the Trellix researchers revealed that 96% of CISOs (who have suffered at least one security incident) believe in the need for improvements. However, 52% of the respondents claim that their organizations have meagre to no technical knowledge on how to tackle challenging security incidents.
According to the aforementioned survey, 48% of security leaders believe that their organizations are majorly based on manual processes, which eventually makes it more difficult to identify and fix cyberattacks quickly.
Moreover, 44% of respondents attribute the inability to tackle cybercrime to inadequately documented and executed procedures, while 44% caution that disjointed security controls result in a deficiency of context.
According to Jake Moore, global cybersecurity adviser at ESET, better investment in security is significantly crucial for companies, taking into account the increased sophistication in cyber activities.
"Furthermore, now with the introduction of AI threats we are seeing cyberattacks become even more relentless and powerful[…]Companies need to bear in mind that the cost of recovery from an attack usually outweighs the cost of preventive security measures,” he says.
Organizations find it challenging to identify and address cybersecurity problems due to a lack of technological resources, but it can also be challenging when security professionals are overworked or underequipped. More than half of those surveyed (52%) said that their organization's security problems were caused by vulnerabilities in their security capabilities.
However, nearly half of the respondents that they had not properly enabled their detection policies or configured their IT stacks. Forty percent more claimed that their security and IT systems do not provide "adequate visibility" of occurrences.
Moore further warns, "Neglecting cybersecurity in terms of the people and process can leave a business dangerously exposed to preventable or mitigable attacks with potentially severe consequences."
In today’s digital age, data is the new oil. It is the lifeblood of businesses and organizations, and its protection is paramount. Cybersecurity threats are rising, and CISOs are under immense pressure to ensure their organization’s security posture is robust. Security data lakes are emerging as a powerful tool that can help CISOs and other security leaders drive accountability.
Security data lakes are an architecture that lets security leaders consolidate security data regardless of quantity and variety, making it possible to drive real accountability across their organization. Security data lakes help achieve this in two ways:
Separate storage from computing, which makes it cost-effective to store security data at scale and for longer periods.
Make security data part of a company’s general-purpose analytics platform, which allows for additional context and delivering insights via standard reporting tools.
CISOs employing security data lakes should think about accountability, a powerful way to improve their overall security posture. Here are three examples of how security data lakes help CISOs and other security leaders drive accountability:
Most companies select and evaluate security vendors based on simple criteria, like whether they support certain data sources and applications. A lack of information keeps decision-makers from evaluating vendors on more meaningful factors like threat detection performance or vulnerability prioritization accuracy.
Security data lakes let teams identify gaps between the insights vendors provide and what an organization actually experiences. Analyzing data from a ticketing system, for instance, lets the team see how many threats detected by a vendor were false positives or how many vulnerability findings are irrelevant.
A security product may work great in one company’s environment but less well at another firm. If the team can measure performance across the metrics that matter to the company, it can work with the vendor to help them improve — or determine that the company needs a better tool.
If remediation teams don’t address vulnerabilities quickly enough on a consistent basis, access to historical data helps uncover those problems and identify processes that may need updating to help them work more effectively.
Security data lakes can hold teams more accountable by consolidating security data regardless of quantity and variety, making it possible to drive real accountability across an organization.
By analyzing historical incident response data, teams can identify patterns in attack vectors or vulnerabilities that led to incidents. This information can be used to improve incident response processes or identify areas where additional training is needed.