The Idaptive Analytics Services is our hosted offering that uses machine learning to detect anomalous user activity in real-time to make our Identity Service risk-aware. These services assess risk, based on constantly evolving user behavior patterns. It then assigns a risk score and enforces an appropriate access decision, all while simplifying risk monitoring and analysis.
Industry experts maintain that the great majority of security breaches can be attributed to weak, default, or stolen user credentials. Attacks that involve compromised credentials are often successful, because the attackers have the perfect camouflage; they appear to be legitimate users. Since the accounts being used are legitimate, these attacks raise no suspicion--all that the network admins see appears to be normal user activity.
Idaptive Analytics Services break this cycle by utilizing machine learning to evaluate access requests. In real time, the Service can determine the likelihood of whether a request is coming from a real, legitimate user or from an attacker who has compromised that user’s account.
Based on the user’s access risk score, the Analytics Services can determine whether to require additional authentication—or block access, entirely. Machine learning within the Idaptive Identity Services automatically creates access profiles that are based on user behavior. Risk scores are then assigned to each access request, across cloud and on-premises applications, VPN, servers, shared account checkout, and more.