Abstract
An entity risk score can be determined based on how an entity interacts with an organization’s computing resources. The entity risk score can be adjusted based on a rule hit score (RHS), which determines how many rules are triggered by the entity’s interactions with the organization’s computing resources. A value of the RHS can be determined using a bipartite graph that includes information for a certain time interval. The RHS value, and how the RHS value change over time, can be used to alter the entity risk score.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Joisha, Pramod and Peacock, Timothy, "Using Artificial Intelligence to Adjust Entity Risk Scores based on Rule Activity", Technical Disclosure Commons, (November 14, 2024)
https://www.tdcommons.org/dpubs_series/7528