How risk assessment for UEBA (user entity behavior analytics) works is not unlike how humans assess risk in our surrounding environment. When in an unfamiliar setting, our brain constantly takes in data regarding objects, sound, temperature, etc. and weighs different sensory evidence against past learned patterns to determine if and what present risk is before us.
A UEBA system works in a similar manner. Data from different log sources, such as Windows AD, VPN, database, badge, file, proxy, endpoints, etc. are ingested. Given these inputs and learned behaviors, how do we fuse the information to make up a final score for risk ranking? source
