What is SIEM good for? – The Evolution of IT Security: From SOC to AI-Driven Protection
In a recent episode of the Deutsche Telekom IT Solutions Unmute All podcast, host Péter Civin sat down with Attila Kocsárdi, a cybersecurity expert, to discuss the evolving landscape of IT security. Their conversation explored how Security Operations Centers (SOCs) have transformed over the years, the role of modern detection tools, and the increasing reliance on AI-driven security solutions. Throughout the discussion, Attila provided deep insights into the real-world challenges of cybersecurity and how organizations are adapting to new threats.
Understanding the SOC: Security Operations Center
One of the key topics was the Security Operations Center (SOC), which plays a critical role in detecting and responding to cyber threats. As Attila Kocsárdi explained, SOCs were originally responsible for both physical and IT security, but they have since evolved to focus solely on cybersecurity. Their primary function is to detect suspicious activity and determine whether an alert is a false positive (FP) or a real security incident. Traditional security tools like Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) are used to analyze network traffic and identify potential threats.
The Role of SIEM in Log Analysis
Security Information and Event Management (SIEM) solutions collect logs from various sources, such as firewalls, antivirus systems, and endpoint devices, to provide a comprehensive view of potential threats. However, as Péter pointed out during the discussion, the vast amount of log data can make manual threat detection impractical. SIEM systems rely on correlation rules to filter out irrelevant alerts, but fine-tuning these systems remains a challenge. Analysts must strike a balance between detecting real threats and avoiding unnecessary noise.
EDR and XDR: Modernizing Threat Detection
A major shift in cybersecurity has been the adoption of Endpoint Detection and Response (EDR) and Extended Detection and Response (XDR) solutions. Unlike traditional security measures that focus on perimeter defense, EDR tools monitor user behavior directly on endpoints, such as employee workstations. XDR takes this a step further by integrating data from IoT devices, cloud environments, and network traffic. As Attila emphasized, this holistic approach significantly improves an organization’s ability to detect and mitigate sophisticated cyber threats.
Automation and AI in Security Operations
With cyberattacks becoming increasingly complex, AI and automation are now essential components of security operations. AI-driven security systems can learn normal user behavior and detect deviations that may indicate an attack. According to Attila, one of the biggest advantages of AI is its ability to identify “low and slow” attacks—where hackers act subtly over an extended period to evade detection. Machine learning models help security teams reduce false positives, focus on real threats, and automate incident response, allowing for faster and more effective mitigation.
Conclusion: The Future of Security Operations
As cybersecurity threats continue to evolve, managed security service providers (MSSPs) are expected not just to detect incidents but also to actively neutralize threats in real time. Platforms like XSIAM (Extended Security Intelligence and Automation Management) are shaping the future of cybersecurity by integrating AI-powered detection with automated response mechanisms. As discussed in the podcast, the shift from reactive detection to proactive protection is becoming a necessity. Organizations that embrace automation and AI-driven security will be better positioned to handle the ever-growing complexity of cyber threats.
Listen to the episode here (Hungarian): https://www.deutschetelekomitsolutions.hu/podcasts/mire-jo-a-siem/