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Security operations centres (SOCs) are at the centre of the organisation’s cybersecurity, which monitor threats, sort through alerts and coordinate responses. These traditional SOCs depend on manual processes, leading to fatigue, slow response time and other operational inefficiencies. With the growing, more frequent and complex threats, SOCs are finding it difficult to handle due to a lack of expert analysts.

With the advent of artificial intelligence and machine learning, SOCs are being automated, increasing accuracy and efficiency, decision-making and other proactive security measures. This article by Pristine Market Insights explains the benefits and challenges of AI SOCs and the future advancements that may drive AIin cybersecurity market.

What is an AI SOC?

An AI-powered SOC is a modern security operation centre that automates threat detection, investigation, and response tactics with the use of artificial intelligence, machine learning, and behavioural data analysis. They uncover hidden hazards by connecting the dots between unrelated alarms that human analysts may overlook. With AI SOCs, security teams get more insight into threat detection, resulting in a more robust cybersecurity defence system. 

Why Traditional SOCs Fall Short?

There are certain fallbacks in traditional SOCs which hamper their effectiveness in today's increasing threat landscape. Alert overload is one of the pressing issues, where analysts are bombarded with thousands of alerts, which may include some false positives as well, leading to fatigue. Analysts also spend a lot of time on repetitive manual tasks. This slows down the operational efficiency, and highly skilled cybersecurity professionals are consumed with these routine tasks, not letting them focus on high-priority threats. This also results in slow response time, an increase in mean time to response (MTTR), which can expose the organisation to greater loss due to a threat. Furthermore, response time is slowed down as analysts lack proper guidance while evaluating some ambiguous threats.

Benefits of AI-Powered SOCs:

AI-powered SOCs boost cybersecurity by detecting threats faster and more accurately. Using AI helps teams respond quickly and stay ahead of attacks. Here are the key benefits of AI-driven security operations.

Enhanced Threat Detection and Predictive Analysis

Behaviour analytics helps to detect suspicious behaviour within an SOC by identifying patterns from the ongoing activity. They can identify any deviation and signal potential threats. From the historical attack data, AI models can predict vulnerabilities and thus strengthen the defence.

Faster Incident Response

Every second is of utmost importance in cybersecurity. AI-driven SOCs reduce time to a greater extent by automating investigation. They can isolate the affected system and contain threats. This reduces the impact of the incident on business operations.

Operational Efficiency and Resource Optimisation

Compared to traditional SOCs, AI-driven SOCs have decreased mean time to detect (MTTD) and respond (MTTR) to threats. Tasks like triaging, investigating and mitigating threats are made easy with AI-automation for the security teams. Without even increasing the head count of the organisation, in this challenging time of shortage of skilled cybersecurity personnel, teams can work efficiently on any urgencies or strategic projects.

Risk Reduction

Due to early threat detection, there are fewer security breaches. Even if any breach occurs, its impact is low due to faster containment or faster incident response time.

Challenges of Integrating AI in SOCs:

Integrating AI in SOCs comes with hurdles like data quality issues, high costs, and the need for skilled experts. These challenges can slow adoption and impact effectiveness. Here are the main obstacles to consider.

Data Quality and Availability

AI requires a large amount of high-quality data to function accurately, . Quality data helps models integrated with AI to learn and adapt to prevent further threats. And sufficient quantity of data enables it to provide accurate threat detection.

Integration Complexity

Significant time and expertise are required to integrate AI into the existing security system. There should be seamless compatibility between the AI systems and the current security infrastructure for effective results.

Human-AI Coordination

SOC relies on human decision-making for improved security results. You cannot rely totally on outcomes generated by AI. No doubt, human-led operations with AI support can handle novel threats and strategic security initiatives.

False Positives or Over-Automation

Lack of proper training, AI can generate a lot of alerts or automate decisions without proper analysis of the premise. There are some alerts which do not pose any security risk in reality, but may seem like a potential threat, which are known as false positives. Dealing with these false positives can be tedious.

Addressing Regulatory and Compliance Considerations

Managing data and compliance with the evolving nature of SOCs will be a critical challenge. For a strong security posture, firms must adhere to the regional laws and regulations. Balancing the adoption of new technology along with strict regulatory requirements is necessary for providing the necessary security capabilities.

The Future

AI will continue to bring transformative changes in SOC operations. Here’ a quick look at how the security operations system will look with more advancements in AI.

 Autonomous SOCs

If put in simple words, autonomous SOC is a highly automated, 24/7 digital, tireless teammate, with human capabilities that help organisations by automating routine tasks initially performed by human analysts. It reduces alert fatigue by filtering and prioritising genuine security concerns.

Threat Intelligence in Real-Time

The future of AI-driven SOCs will be built on the foundation of real-time threat intelligence. It plays a vital role in SOC operations. This system will work by constantly ingesting data related to threats from cloud services and network traffic from around the globe, and thus help in detecting and mitigating emerging threats before they escalate.

Conclusion

AI will not replace humans in SOC, but it will work alongside security professionals, by automating routine, repetitive tasks. Though AI can analyse an enormous amount of data faster than humans, it does not have any contextual understanding that humans have and which is needed at some point. AI SOCs cannot weigh the risks and think critically before making any decisions.

On the darker side, attackers also use AL to automate malware creation and uncover new vulnerabilities. Attackers are becoming creative, and tackling them needs creative approaches. Humans will continue to contribute by training, validating and governing the AI-driven SOC models. The future is about human-AI collaboration, working on combining their strengths and not about choosing between human and AI. This is a commitment towards a goal to safeguard the digital assets and business operations against cyber threats.