Have you ever desired to have an aide at your security operations centers (SOCs) — particularly one who never calls in sick, has a bad day or takes an extended lunch break? Your aspiration might come to fruition soon. Predictions for 2025 in the realm of cybersecurity indicate that AI-driven SOC “co-pilots” are at the forefront, often hailed as transformative tools.
According to Brian Linder, the Cybersecurity Evangelist at Check Point, “AI-driven SOC co-pilots will have a significant impact in 2025, assisting security teams in prioritizing threats and converting overwhelming datasets into useful intelligence. This will revolutionize SOC efficiency.”
What constitutes an AI-driven SOC co-pilot?
AI-driven SOC co-pilots are generative AI tools that leverage machine learning to aid security analysts in operating and overseeing the SOC. Tasks typically handled by co-pilots include threat detection, incident management, alert triaging, forecasting new attack trends and patterns, and automating responses to threats. Co-pilots can either be custom tools developed in-house to meet specific requirements or off-the-shelf cybersecurity co-pilots like Microsoft Copilot.
For instance, a co-pilot can evaluate alerts and utilize AI to forecast those with the highest priority. This helps mitigate a common issue in SOCs: false positives. By focusing on alerts that pose a genuine threat, analysts can allocate their time more effectively towards actual threats, thereby enhancing their success in containing the threat.
Co-pilots can assume various roles within a SOC. Analysts can engage with the co-pilot similarly to how many individuals interact with ChatGPT, assigning it particular tasks such as incident response. Analysts provide information about a specific incident, and the co-pilot analyzes data to propose potential causes and appropriate responses. Additionally, co-pilots can automate segments of the workflow without requiring human intervention, like monitoring current firewalls and identifying vulnerabilities.
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Advantages of employing AI-driven SOC co-pilots
Businesses integrating AI-driven co-pilots into their SOC enjoy numerous benefits. Common advantages include:
- Enhanced efficiency: Due to their ability to handle significantly larger data volumes than even the most efficient cybersecurity analyst, co-pilots accomplish more work in less time. The collaboration of humans and machines enables co-pilots to efficiently monitor the SOC with fewer human resources.
- Increased time for cybersecurity professionals to tackle high-level assignments: By delegating manual and repetitive tasks to co-pilots, analysts have more time for strategic and analytical responsibilities. Analysts are more engaged when their tasks are intellectually stimulating, thereby reducing burnout.
- Reduced errors: Humans are prone to errors, especially with manual tasks like log reviews. While AI tools are reliant on the algorithm’s sophistication and the training data used, they can often identify patterns that elude human detection. This minimizes errors and prevents incidents that could lead to a breach or attack.
- Swift response to threats: Whereas humans might overlook vulnerabilities or respond slowly, co-pilots leverage automation to react promptly and provide immediate notifications. Co-pilots are always available, ensuring faster response times as they do not require breaks.
- Alleviated impact of workforce shortages and skill gaps: Unfilled cybersecurity positions or mismatches in analysts’ skills pose risks to the company. AI-driven co-pilots alleviate staff shortages by undertaking various manual tasks, resulting in expanded coverage for the SOC.
Will AI-driven SOC co-pilots supplant humans?
While co-pilots can assume many manual and repetitive tasks currently handled by humans, the apprehension regarding AI replacing human necessity in the SOC is unlikely to materialize. Enabling co-pilots to operate autonomously without human oversight would probably be ill-advised. Collaborative efforts between analysts and co-pilots can reduce risks, enhance responses, and bolster employee satisfaction.
Even though co-pilots may serve as the initial line of defense in the SOC, organizations should configure generative AI tools in a manner that retains humans as the ultimate decision-makers. For instance, an analyst might automate monitoring and prioritization of alerts based on specific criteria with an AI-driven co-pilot. Nonetheless, when threat actors adopt new strategies, analysts may need to adjust the criteria to counter the latest threats. Upon identifying a high-priority alert, the human can seek the tool’s analysis and recommendations. Subsequently, the analyst utilizes human judgment to make informed decisions and directs the tool to implement the next action, like temporarily halting network operations.
Implementing AI-driven co-pilots in the SOC
When deploying co-pilots, consider commencing with a limited scope and a specific use case. Many organizations initiate with a commercial product, leaving room for potential development of a proprietary tool in the future. Identifying time-consuming tasks within the SOC, particularly those prone to errors or dissatisfaction among analysts, aids in selecting the initial use case. Post-launch, a single analyst can gather feedback and make necessary adjustments.
Upon achieving success, expand the utilization of co-pilots to encompass more analysts and use cases. By adopting a methodical approach to co-pilot implementation and consistently seeking input from analysts, businesses can forge a collaborative relationship between analysts and co-pilots. This synergy enhances job satisfaction for humans while fortifying organizational security.