Human factor as previously remains the primary threat for any kind of business. The UBA system considers patterns of human behavior. Using computational algorithms and statistical analysis it reveals significant anomalies of these patterns, which carries potential threat. Instead of collecting information about gadgets and events, UBA focuses on people, using these gadgets.
Security systems collect huge amount of various data, therefore manual analysis of them may take years or even decades. Besides, there is no clear understanding, what particular data foreshadows potential attack. UBA solution focus on behavioral patterns and their violations, which are bright markers of increasing risk. Security service receives visual reports, containing average risk level in company and separated TOP-list of most unreliable employees. With this information, the security officer can carry out preventive work in a timely manner and neutralize the existing risk.
How UBA technology is represented on the market?
Today there are various solutions that make it possible to use UBA technology. With their help, you can conduct in-depth analytics, build patterns of users behavior and prevent possible threats. However, due to the high cost of such solutions, companies prefer combined functionality. For example, UBA fetures integrated with DLP system or employees control system.
UBA and Falcongaze SecureTower
In the latest version of SecureTower was added UBA-module Risk analysis. It allows to monitor abnormal and potentially dangerous for organization changes in employees behavior.
The module identifies total level of risk coming from employees, based on incidents. Information security officer can configure the level of risk for each specific incident. As a result, a TOP-list of employees representing an increased threat is formed. Changes in risk levels are automatically reflected in the dynamic graph of employee temporal trends.
Risk analysis module automatically generates all the necessary information and reports to carry out research of trends in user behavior.