Cybersecurity threats are becoming sophisticated, and security leaders are turning to AI-powered solutions to increase their defenses.
As the applications of generative AI in security continue to expand, the next-generation Security Operations Center (SOC) is poised to revolutionize how organizations detect, investigate, and respond to threats.
This transformation is possible with Network Detection and Response (NDR), a critical component that enhances the capabilities of AI-powered SOCs, which enables them to operate with efficiency and effectiveness.
The Vision of a Next-Generation, AI-Powered SOC
Before we go right into the content, some might be curious to know NDR meaning in cybersecurity. NDR advanced machine learning and artificial intelligence tools that use different types of tactics, techniques, and procedures mapped in the MITRE ATT&CK framework to detect threat behaviors.
Imagine a SOC that can go through large amounts of data, identify patterns, and predict threats with minimal human intervention. This vision is close to reality. Today, AI empowers SOC teams in three primary ways:
Efficient Data Processing: AI can process and analyze data faster than any human analyst, making it possible to identify potential threats almost instantly.
Correlation of Multiple Detections: AI can link various, seemingly unrelated detections to provide a comprehensive view of malicious activity, improving the speed and accuracy of threat identification.
Automated Script and Rule Development: Security analysts can leverage AI to develop and refine scripts and detection rules, enhancing the SOC’s ability to respond to evolving threats.
On the horizon, two more capabilities are expected to enhance SOCs further:
Natural Language Explanations: AI tools, using large language models (LLMs), will soon be able to explain detections in natural human language, making it easier for analysts to understand and act on complex threats.
AI-Based SOC Co-Pilots: These tools will work under human supervision to automate incident response and threat hunting. They will gather data, analyze detections, make recommendations, and execute runbooks with human approval, significantly reducing the workload on human analysts.
Critical Data Sources for the Next-Gen SOC
A next-gen SOC relies on various data sources to function effectively. Traditionally, most SOC data comes from Endpoint Detection and Response (EDR) tools, which are essential for detecting malicious behavior on endpoints. However, not all endpoints can run EDR agents, leading to significant visibility gaps. According to telemetry from ExtraHop, up to 60% of endpoints may lack EDR coverage.
This is where network data becomes indispensable. NDR solutions fill these visibility gaps by monitoring network traffic for signs of malicious activity. Network data can detect threats that EDR might miss, such as Kerberos Golden Ticket attacks, Cobalt Strike beaconing, lateral movement, and file share data encryption. The network is the backbone of all digital communication, and monitoring it provides a comprehensive view of all interactions within an organization.
When EDR data is combined with NDR insights, SOCs gain a complete picture of an attack. While EDR tells you who the characters are in an attack, NDR shows their relationships and interactions, effectively turning data into a narrative that security teams can act upon. NDR is crucial for filling in the gaps and providing the contextual information necessary for a comprehensive security posture.
The SOC Visibility Triad
To achieve maximum security, a SOC must deploy a combination of tools that provide visibility across the network, endpoints, and logs. This triad consists of:
Network Detection and Response (NDR): Offers an aerial view of all interactions on the network, detecting activities that might go unnoticed by endpoint or log-based solutions.
Security Information and Event Management (SIEM): Collects and correlates log data from various sources, providing a centralized view of security events and facilitating more effective incident response.
Endpoint Detection and Response (EDR): Provides a detailed, ground-level view of processes running on endpoints, capturing interactions and activities that occur on each device.
This triad enables security teams to answer critical questions during incident response, such as: What did an asset or account do before and after an alert? When did the malicious activity start? By integrating these tools, SOCs can ensure no threat goes undetected, regardless of where it originates.
The Unique Role of NDR
NDR is unique and indispensable in the SOC visibility triad. While EDR and SIEM are critical, they can miss certain types of threats that NDR can detect. For instance, exploits that operate at a device’s BIOS level can evade EDR detection, and malicious activities might not always be logged. However, these activities will be visible on the network as soon as the compromised device interacts with other systems.
Moreover, advanced attackers often use encrypted HTTPS tunnels to blend in with regular traffic, launching command-and-control (C2) sessions and exfiltrating data without triggering perimeter defenses. NDR solutions, such as those provided by Stellar Cyber, are adept at detecting these behaviors, ensuring that even the most sophisticated attacks are identified and mitigated.
Enhancing SOC Capabilities with AI-Driven NDR
Effective AI-driven NDR platforms collect and analyze the correct metadata, enriching it with AI-derived security insights. This allows for real-time detection of attackers and thorough incident investigations. The quality and reliability of the data used to train AI systems are crucial. The better the data, the more accurate and effective the AI’s analysis and response.
AI models that analyze and correlate threat intelligence across multiple domains—network, endpoint, cloud workload, applications, and data centers—provide better context and enhance the SOC’s overall effectiveness. For instance, Stellar Cyber’s AI-driven NDR platform integrates data from various sources, ensuring comprehensive coverage and timely detection of threats.
Combatting AI-Powered Cybercriminals
As cybercriminals increasingly leverage AI to enhance their attacks, it becomes imperative for organizations to adopt AI-powered defenses. AI-powered criminals use advanced techniques to infiltrate networks, exfiltrate data, and launch sophisticated ransomware attacks. To counter these threats, AI-powered SOCs must be equally advanced, employing AI-driven tools to detect, respond to, and mitigate cyber threats effectively.
AI-powered SOCs can dramatically reduce the mean time to resolve (MTTR) critical incidents, cutting down response times from days or weeks to mere seconds or minutes. By transitioning from a reactive, manual security operations model to a proactive, AI-driven approach, organizations can stay ahead of cybercriminals and maintain a robust security posture.
Conclusion
Network Detection and Response (NDR) plays a major role in enhancing the capabilities of AI-powered, next-generation SOCs. It provides comprehensive visibility, enriches data with AI-driven insights, and enables faster, more accurate threat detection and response. So, integrating NDR into AI-powered defenses will be necessary for organizations that seek to maintain a strong and resilient security posture.
