Analysis of User Behavior, Pattern & Trends to Form an Extra Layer of Protection from Insider Threats
Enhanced Protection from Social Engineering and Mitigating Human Risk Factor
The advance threat correlation feature allows us to relate feeds from a user and provides a holistic view of an entity for better analytics.
Our AI-based analytics system establishes a behavioral baseline that defines how they “normally” behave. It then identifies anomalies that deviate from that baseline, this helps to alert and respond in case of a deviation beyond the threshold.
Our sophisticated statistical and quantitative models, such as Machine Learning and Deep Learning uses data collected from log sources & provides advanced analytics to complement the traditional alert and response mechanisms.
It helps to organize the incidents which are particularly abnormal, suspicious, or potentially dangerous in the context of your organization. It can go beyond baselines and threat models by adding data about the organizational structure like the criticality of assets and the user roles and access levels of specific organizational functions.
Monitoring and analyzing end-users within the organization helps to mitigate the risk caused by social engineering attacks, rogue employees, and compromised users. Our UEBA solutions observe and alert in case of deviation from normal baselines and prevent attacks originating from inside.
UEBA works along with existing security products like DLP, Firewall and SIEM to enhance the quality of response and alerts.
Enhanced ROI on your cyber security investment through an additional layer of security
Enabling prioritized and contextual incident response
Mitigating social engineering and human risk factors
Reduction of the most challengeable attack surface i.e. compromised end-user
Reduction in events and thus increased productivity of security operations
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