Intent Recognition for Adversarial Groups using Dynamic, Predictive Threat Heatmaps
Abstract
This project aims to develop a framework for detecting and identifying adversarial intentions performed by groups of multiple coordinated agents (red) against an own team (blue), consisting of either one or multiple agents. Assuming an environment with both adversarial as well as neutral agents, a key challenge is to properly disambiguate between malicious and benign intentions. In addition, maneuvers that may initially appear benign could actually be deceptive actions aimed at diverting attention from a malicious intent. In prior ONR-funded research, we developed HMM-based capabilities for recognizing intentions of single agents, from overt behaviors, with agents reduced to a simplistic point form representation. In this project, we aim to expand our work along several directions in order to: 1) design a more realistic agent model that includes systems for sensing and defense, and their structured coverage areas, 2) recognize intent in the presence of coordinated groups/swarms of adversarial agents, 3) enable detection of both overt and deceptive intent, and 4) provide recommendations for actions that minimize/reduce potential threats.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 05, 2021
- Source ID
- N000142112234
Entities
People
- Monica Nicolescu
Organizations
- Nevada System of Higher Education
- Office of Naval Research
- United States Navy