What is Behavioral modeling?
Behavioral modeling involves creating mathematical or computational models that simulate and predict human behavior. When applied to cybersecurity, organizations can better detect and prevent potential cyber threats by analyzing and understanding the patterns and behaviors of personnel, including system administrators, software developers, and end users.
Behavioral modeling focuses on identifying anomalies in behavior. For instance, if an employee suddenly starts accessing sensitive information or unauthorized files during unusual hours or from unfamiliar locations, it may be a sign of malicious intent or a potential security breach. By applying behavioral modeling techniques, cybersecurity teams can develop profiles of normal behavior and establish a baseline for comparison. Any deviation from this baseline can trigger alerts, allowing organizations to quickly respond to and manage potential risks. Moreover, organizations can use these models to develop effective interventions, design better policies, or even improve the performance of artificial intelligence systems.
By leveraging advanced data analytics and machine learning algorithms, the Resolution Intelligence Cloud™ platform helps organizations understand and predict the behavior of their systems and users. In fact, the platform can track behavior for an attribute at any level — for example, environment, user, IP, machine, account — to provide a comprehensive view into their security landscape as well as valuable insights into patterns and trends across their overall digital infrastructures. By enabling organizations to baseline normal behavior and detect deviations in real-time, the platform can help ensure that no suspicious or anomalous activity goes unnoticed.
The proactive nature of behavioral modeling and analytics helps organizations identify anomalies, potential threats, and vulnerabilities and make data-driven decisions to manage risk and improve their overall security posture. Additionally, security and IT teams can use the insights gained to identify inefficient processes and areas for improvement to optimize overall digital operations.