SOC of the future: the AI-driven SOC

Why traditional SOCs are struggling

Traditional SOCs face an unwinnable battle; an explosion of threat data, a dramatic increase in attack sophistication and the competitive skills market are just three challenges organisations face. Making talent difficult to find and harder to retain. Running a traditional SOC means:

• Alert fatigue: the sheer volume of alerts, many of them being false positives, leads to analysts being overwhelmed and missed threats & attacks.
• Slow response times: manually analysing and responding to incidents & alerts is time-consuming and provides a critical window of opportunity to threat actors.
• Human error: the volume of alerts & incidents, managing & understanding mountains of threat intelligence data and endlessly updating detection rules leads to higher risk and more breaches.

AI: driving innovation & efficiency

Leveraging AI & automation allows a SOC to make use of intelligence & data that is not possible in a traditional SOC.

AI and automation offer a number of advantages to a SOC, including threat detection that identifies malicious behaviour and threat actors otherwise undetectable by humans alone, and predictive analytics that can proactively recognise and flag emerging threats based on historical data. Additionally, AI can automate routine tasks such as identifying and blocking malicious IP addresses, freeing up analysts to focus on in-depth investigations and improvements. AI can also process huge quantities of threat data from many sources, offering a real-time picture of the current threat landscape and its relevance to the organisation. Finally, AI helps to reduce the number of false positives, allowing analysts to be more efficient and productive.

The advantages of AI and Automation include threat detection, predictive analytics, identifying and blocking malicious IP addresses,offering a real-time picture of the current threat landscape and reduce the number of false positives.

Practical applications in the SOC

The following is possible within the AI-driven SOC of the future:

• Behavioural analytics: identifying compromised accounts or insider attacks based on unusual user activity like device location and system usage.
• Security Orchestration, Automation, and Response (SOAR): automating incident response capabilities & workflows leads to faster containment and remediation.
• Threat hunting: proactively identifying more threats by leveraging AI as part of threat hunting capabilities.
• Vulnerability management: Risk-based prioritisation of vulnerabilities based on exploit likelihood is being leveraged within workflows.
• Large Language Models: provide additional insight into incidents as they occur assisting analysts in real-time decision making.

Human expertise continues to be essential

AI brings benefits in efficiency and scale but is not a replacement for human expertise. Analysts remain crucial for contextual understanding, as humans are needed to understand the intent behind anomalies and data. Complex investigations and incidents continue to be led by analysts and security engineers who make business-critical decisions. Furthermore, technical teams ensure that organisations continue to use AI responsibly and ethically.

The future of the SOC: the best of both worlds

The future of the SOC relies on the effort between security teams and the AI they choose to leverage. Automating routine tasks, enhancing threat detection and further enabling threat hunting activities with AI ensures security analysts and engineers can focus their time on high value, high impact tasks leading to a stronger security posture for organisations.

Real-world impact

Download our whitepaper to see how Qodea's Managed Detection and Response (MDR) services can help your organisation navigate the complexities of modern cyber threats and develop a robust security posture.

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