Training artificial intelligence (AI) and machine learning (ML) models to provide enterprises with hybrid cybersecurity at scale requires human intelligence and intuition. When human intelligence and intuition are combined with AI and ML models, subtleties in attack patterns that are missed by numerical analysis alone can be detected.
Data scientists, security analysts, and threat hunters with extensive experience make sure that the data used to train AI and ML models enables a model to accurately identify threats and minimize false positives. The future of hybrid cybersecurity is defined by combining human expertise, AI, and ML models with a real-time stream of telemetry data from enterprises' numerous systems and apps.
Benefits of hybrid cybersecurity
One of the fastest-growing subcategories of enterprise cybersecurity is the integration of AI, ML, and human intelligence as a service. The service category that benefits the most from businesses' need for hybrid cybersecurity as a component of their more comprehensive risk management strategies is managed detection and response (MDR). Client inquiries about this topic increased by 35%, according to Gartner. Additionally, the report predicts that the MDR market will generate $2.2 billion in revenue in 2025, up from $1 billion in 2021, representing a compound annual growth rate (CAGR) of 20.2%.
The MDR services that rely on AI and ML for threat monitoring, detection, and response functions will be used by 50% of organizations by 2025, the report further reads. To find threats and halt breaches for clients, these MDR systems will increasingly rely on ML-based threat containment and mitigation capabilities, bolstered by the expertise of seasoned threat hunters, analysts, and data scientists.
Efficient against AI and ML attacks
In organizations with a shortage of data scientists, analysts, and experts in AI and ML modeling, hybrid cybersecurity continues to rise in importance. VentureBeat, a cybersecurity news portal, spoke with CISOs from small, rapidly expanding companies to mid-tier and large-scale enterprises, and they all emphasized the need to protect themselves from faster-moving, deadly cybercriminal gangs that are developing their AI and ML skills more quickly than they are. “We champion a hybrid approach of AI to gain [the] trust of users and executives, as it is very important to have explainable answers,” stated AJ Abdallat, CEO of Beyond Limits.
Within one hour and 24 minutes of the initial time of compromise, cybercriminal gangs with AI and ML expertise have demonstrated that they can move from the initial entry point to an internal system. A 45% increase in interactive intrusions and more than 180 tracked adversaries were noted in the CrowdStrike 2022 Global Threat Report. Staying ahead of threats is not a human-scale issue in this environment. It requires the potent fusion of human expertise and machine learning.
Endpoint detection and response (EDR), extended detection and response (XDR), and endpoint protection platforms (EPPs) powered by AI and ML are proving successful at quickly spotting and thwarting new attack patterns. However, they still need time to process information and become aware of fresh threats. Convolutional neural networks and deep learning are used in AI and ML-based cybersecurity platforms to help reduce this latency, but hackers continue to develop new methods faster than AI and ML systems can catch up.
As a result, even the most sophisticated threat monitoring and response systems relied upon by businesses and MDR providers find it difficult to keep up with the constantly changing strategies used by malicious hackers.
Lowering the possibility of a business disruption
Boards of directors, CEOs, and CISOs are discussing risk management and how hybrid cybersecurity is a business investment more frequently as a result of the possibility of a devastating cyberattack having an impact on their ongoing business operations. CISOs tell VentureBeat that board-level initiatives for cybersecurity in 2023 will include hybrid cybersecurity to protect and increase revenue.
Hybrid cybersecurity will remain a thing. It aids businesses in overcoming the fundamental problems they face in defending themselves against cyberattacks driven by AI and ML which are getting more and more sophisticated. CISOs who lack the resources to scale up AI and ML modeling rely on MDR providers who offer services that include AI and ML-based EPP, EDR, and XDR platforms.
By removing the difficulty of locating skilled AL and ML model builders with experience on their key platforms, MDRs allow CISOs to implement hybrid cybersecurity at scale. For CISOs, hybrid cybersecurity is essential to the long-term success of their companies.
