AST April 2018 Magazine AST April Magazine (3.30.18) | Page 14

GRA applies a risk-based Volume 22 approach for certifica- tions, access requests and approvals to identify and remove excess access, ac- cess outliers, and orphan and dormant accounts. April 2018 Edition By uniquely combining UEBA with IdA, GRA iden- tifies with precision the compromise and misuse of identity, which is the root of most modern cyber threats. Taking machine learn- ing to the next level, GRA includes 300+ ready-to-use machine learning models for on-premises, cloud or hybrid environments. Gurucul STUDIO, a unique part of GRA, enables orga- nizations in high security industries like government, intelligence, law enforcement, etc. to define custom machine learning models to meet their specific re- quirements, customize risk weightings and develop their own machine learning models without any cod- ing. An industry-first, GRA’s Self-Audit capabilities em- power government agency end users to monitor their own accounts for anomalous and suspicious access and activity. Another area where GRA excels over the compe- tition is in privileged access management (PAM). Traditional PAM solutions perform discovery at the account level. However, many organizations assign high privi- lege entitlements to “normal” accounts as well. Manually discovering high risk entitlements that ex- ist outside of privileged accounts is impossible. Consider an organization with 10,000 identities, where each identity has 10 accounts with 10 enti- tlements. That would equal 1 million entitlements. 12