75% of data breach incidents are caused by insiders. Would you like to detect who and when as quick as possible?
The complexity of analyzing insider threats makes it almost impossible to detect anomalous user behavior by using traditional rule-based models.
With its longstanding machine learning capability, HanSight leverages advanced algorithms to analyze up to two years of historical data to accurately identify anomalous user behavior from massive data.
A massively scalable and readily available data platform is required to support advanced analytics—one that provides users accessibility, quality and data coverage from a range of security and enterprise systems.
Designed to support AD/LDAP and other major business information regulatory systems, HanSight UBA is easy to deploy and can benefit customers in a very short time.
Relying on HanSight’s sophisticated machine learning algorithms, HanSight UBA is able to accurately locate anomalous user behavior within an organization and display the entire lifecycle of security operations unified by continuous monitoring and advanced analytics. This enables customers work out response policies quickly hence to eliminate the data loss risk.
HanSight Enterprise enables us to manage our security incidents in an integrated approach and understand our overall security posture better. HanSight UBA also helps locate malicious insiders, to keep our data safe.
——Information Security director of a large manufacturing firm
Senior security engineers from HanSight have the answer.