Generative AI platforms like ChatGPT are revolutionizing how we access information, answer questions, and even develop software code. It’s no surprise that according to the KPMG Cybersecurity Survey: Security Operations Center (SOC) Leaders Perspective (PDF), two-thirds (66%) of security leaders consider AI-based automation to be very important, both now and in the future, for staying ahead of new threats and increasing the agility and responsiveness of their SOCs. While AI-based automation offers numerous benefits, the reliability of AI-generated recommendations remains a top concern for cybersecurity leaders. This raises the question: What does it take to unlock the full potential of AI in cybersecurity?
Anyone who has explored generative AI platforms can see that AI has the potential to significantly enhance cybersecurity—particularly in querying large datasets, identifying abnormalities, and triggering event-based actions like triaging tickets, alerting teams, or reducing false positives. However, like any technology, AI also introduces new risks and challenges that must be carefully managed. Some key risks include:
- Weaponized AI: Cyber adversaries can leverage AI to develop sophisticated attack methods, including introducing malicious data into training datasets to corrupt AI models, leading to incorrect or dangerous outputs.
- Overreliance on AI: Organizations might become overly dependent on AI systems, believing them to be infallible, which can lead to complacency in human oversight and manual security checks.
- Lack of Transparency: AI systems, particularly those based on deep learning, can be opaque, making it difficult to understand how decisions are made. This lack of transparency can negatively impact incident response and root cause analysis.
- Data Privacy Concerns: AI requires vast amounts of data for training, raising concerns about data privacy and compliance, especially when sensitive information is involved. Furthermore, AI systems may store or process large datasets, making them attractive targets for cybercriminals who seek to steal or manipulate this data.
- Resource Intensity: Implementing and maintaining AI-driven cybersecurity systems can be expensive, requiring significant computational resources and skilled personnel.
Despite these challenges, AI plays a crucial role in modern cybersecurity, offering significant advantages that help organizations protect against increasingly sophisticated threats. Some key benefits of AI in cybersecurity include:
- Enhanced Threat Detection: AI can continuously monitor networks, systems, and devices in real time, detecting threats faster than traditional methods. It can also identify unusual patterns of behavior that may indicate an attack, even if the specific threat is unknown (e.g., zero-day threats). Furthermore, machine learning models can analyze historical data to predict potential threats, allowing for proactive defense measures.
- Automation of Security Tasks: AI automates repetitive tasks such as log analysis, vulnerability scanning, and patch management, reducing the workload on cybersecurity teams. It can also automate initial responses to security incidents, such as isolating affected systems or blocking malicious traffic, enabling faster containment of threats.
- Handling Large Volumes of Data: AI excels at processing vast amounts of data, enabling it to sift through logs, network traffic, and security alerts to identify potential threats with greater speed and accuracy than human analysts.
- Reducing False Positives: By leveraging machine learning, AI can reduce the number of false positives in security alerts, allowing security teams to focus on genuine threats and avoid alert fatigue.
- Proactive Threat Hunting: AI can automatically search for indicators of compromise across an organization’s infrastructure, identifying potential threats before they cause damage.
- Resource Optimization: By automating many aspects of cybersecurity, AI helps organizations optimize their resources, reducing the need for large security teams and minimizing the impact of the cybersecurity skills shortage. With AI handling routine tasks, cybersecurity professionals can focus on more complex and strategic challenges, enhancing the overall effectiveness of security operations.
Currently, most AI strategies are focused narrowly on assisting with specific tasks, and organizations are still evaluating the risks posed by this emerging technology. However, as cyber adversaries increasingly exploit AI, security practitioners must not fall behind. Instead, they should strike a balance between risk and reward to enhance threat hunting and achieve greater operational efficiency.
Related: AI in the Enterprise: Cutting Through the Hype and Assessing Real Risks
Related: Can AI be Meaningfully Regulated, or is Regulation a Deceitful Fudge?
