Advanced Behavioral Analytics to Deter Insider/Internal Threats Market Research

The Hanscom Air Force Base Global Network Systems program office is seeking a solution to prevent, detect, and respond to internal and insider threats to their network. They are specifically interested in implementing User and Entity Behavioral Analytics (UEBA) technology, which uses machine learning and statistical analysis to identify deviations from normal behavior patterns that could indicate a potential threat. The UEBA solution will track all users, devices, and applications within the network and focus on detecting insider threats such as rogue employees or compromised individuals. The goal is to establish a network baseline and apply analytic methods to identify anomalies in traffic patterns. UEBA systems typically consist of three main components: data analytics, data integration, and presentation.

UEBA analytics offer several benefits, including speeding up detection, investigation, remediation, and forensics processes. By correlating and presenting logs in context, analysts receive fewer but more meaningful alerts that are easier to analyze. UEBA also eliminates event fatigue by parsing and aggregating logs from various sources with different formats. This allows for intelligent log collection, reducing the amount of data being analyzed. Additionally, UEBA enables security analysts to derive proactive insights through meaningful analytics by establishing baselines of normal behavior for users, systems, and data interactions.

Overall, the acquisition timeframe for this opportunity is not specified in the summary. The place of performance/delivery is also not mentioned. However, it is notable that Sierra Nevada Corporation (SNC) is leading the MACE team for this evaluation effort.