What is the purpose of behavioral analytics?
Threat actors are getting smarter every day, breaching organizations by compromising credentials and servers. However, attackers still struggle to accurately mimic the behaviors of systems and users. That’s why behavioral analytics is a core tenet for enhanced detection and an important capability of the modern SIEM.
Tracking, monitoring, and alerting about behavioral changes enable SecOps teams to improve signal-to-noise ratio and detect bad actors more quickly and easily. Modern techniques for user and entity analytics (UEBA) include a combination of machine learning, statistics, and aggregations with human-in-the-loop capabilities to determine trends, patterns, and activities. But even with all those capabilities, behavioral analytics alone can’t solve the problem.It must be used in conjunction with threat intelligence and context to accurately inform detections and investigation.
Entity behavior analytics: What are the top challenges for SecOps?
With many tools today, deployment and operations for behavioral analytics are time and resource intensive, in some cases requiring difficult-to-find data science skills.
The rigidity of detection rules can’t keep pace with the constantly evolving threat landscape.
LACK OF INTEROPERABILITY
The need to use multiple SecOps tools disrupts the workflow as analysts must switch between multiple screens to get the job done.
Common use cases for entity behavior analytics in the SOC
Insider threat detection
Behavioral change is a critical indicator of potential abuse by privileged users or unauthorized employee access. Behavior modeling enables organizations to continually learn how users behave, and identify changes that indicate malicious activity including sabotage, theft, or privilege misuse. Behavioral analytics for insider threat detection tracks activities such as what assets are accessed and how frequently a user accesses applications.
The growing number of threat categories and types has far exceeded the scope of predefined rules. Detection capabilities must continually learn and self-optimize to better combat today’s complex threats, such as zero-day exploits. Behavioral analytics improves visibility into noteworthy changes of entities, enabling quick and accurate incident identification. This includes improved identification of spoofed and compromised users, the creation of new super users, or brute-force access attempts.
Data access monitoring
Business-critical data is a key target for all walks of cybercriminals ranging from disgruntled employees to hacker groups. Behavioral analytics support real-time monitoring of critical data resources by tracking data movement. In light of the regulatory environment, behavioral analysis of data access also helps organizations comply with evolving data and privacy regulations such as GDPR, PCI- DSS, and HIPAA.
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