Centrify Analytics Service

Analytics Service from Centrify prevents security violations in real time on the basis of behavior of the user. The intelligent system uses machine learning for risk assessment, based on the analysis of changes of templates of behavior of users. Then she estimates risk and makes the relevant decision - to provide access, to demand additional authentication or to completely block access.

According to the new research Forrester conducted by request of Centrify two thirds of the organizations on average five times faced security violations in the last two years. Also, billions of passwords and user names were stolen that increased the number of the attacks and risk of further violations. Strength of these attacks is ideal masking. Malefactors "look" as well as privileged users and do not cause suspicions in IT as all actions to be displayed as normal activity of the user.

Centrify gives to IT an opportunity to break off a cycle of operation and loan of the rights of accounts to stop the attacks which lead to date leaks. A system not only stops abnormal requests of real-time access and also puts a mark on potentially compromised accounts and draws to them attention to IT - accelerating the analysis and minimizing efforts for risks assessment in a modern hybrid IT environment. With the help by machine learning, the IT department is exempted from creation of policy manually for all endpoints, applications, the websites, services and resources.

Development of security policy for employees, contractors, partners and exclusive IT users made security it is more important than the user experience. The behavioural analysis allows users is transparent to interact with a management system for exclusive access when they represent low risk, without complicating thereby work of users and without affecting productivity, but at the same time supporting the high level of protection.

Access on the basis of risk the politician and the choice of actions for which it is necessary to undertake for a certain risk level by risk assessment for end and privileged users gives to IT specialists new opportunities for control.

Examples of access on the basis of risks:

• Uniform login (SSO) for applications: While the behavior of the end user sootvetvut to normal access, it represents low risk and the IT can provide quick access to the applications.
• Multi-factor authentication (MFA) for verification of the password: When the IT administrator checks exclusive credentials or initiates exclusive network connection on the server or from other, not typical resource, the risk level increases and it will be offered to administrator to execute additional authentication.
• MFA for third-party IT: In case of attempt of the malefactor to use third-party credentials from earlier unknown device, access can be completely blocked, stopping the attack before it causes damage.

As this system is a part the Centrify Identity Services platform, clients can implement policy on the basis of risk in the hybrid environment consisting of endpoints, cloud applicaions, IaaS and IT servers and resources for more detailed heuristics and more effective policy. Available as addition to Centrify Identity Service and Centrify Privilege Service, the solution is natural expansion of adaptive multifactor authentication Centrify, adding machine learning which simplifies settings for IT and fixes permanent problems of MFA, simplifying access for end users.