Entity Behavior Analytics allows you to identify all the risky users within the network and take appropriate action whenever there is an anomaly. Each and every behavior deviation is identified and prioritized as per the level of deviation caused. EBA precisely identifies any suspicious activities by tracking user behavior and raises an alert on every instance of a violation. The streamlined monitoring and detection eases the load on analysts by directing the investigation path and providing accurate visibility of the anomaly.
How does behavior analytics work?
EBA monitors the behavior of users and entities of an organization. It processes this information and decides whether a particular activity or behavior could result in a cyberattack. It will identify what could be a threat and what is normal using a variety of analytics approaches including statistical models, and machine learning rules. A signal is raised for each anomaly detected, based on the severity and confidence level, analysts can easily identify and prioritize genuine threats and respond quickly before these potential threats become breaches.
Identify Insider threats
Insider threats can come from any insider within an organization with authorized access to your systems, network and applications. Attackers might also target an unsuspecting insider using privilege escalation, an intrusive method to compromise their system and gain access from outside. With correlation rules and statistical analysis, data from across your entire network is collected to perform behavioral analysis and detect anomalies, alerts analysts about security incidents identified.
Track Unauthorized Data Access and Exfiltration
On accessing any kind of sensitive data an alert is triggered so that security analysts can track down and analyze if there was a security breach and protect the data from infiltrations. You can easily identify all these acts that can sabotage the organization, keep abreast of these attackers and quickly implement counter measures to block access.
Behavioral Profiling and Anomaly detection
Behavioral patterns of users and devices are analyzed to create baselines of normal and expected behavior. All new events are compared against these baselines and any deviation from the expected behavior is considered as an anomaly. A signal will be raised to alert the security team on detecting an anomaly so that an appropriate action can be taken. In addition, it provides visual points through graphs so that analysts can proactively investigate any connected anomalous behavior.