Bio-Inspired Distributed Decision Algorithms for Anomaly Detection
Nina H. Fefferman · 2017
Abstract : This research effort brought together computer scientists and biologists to investigate the potential for self-organizing anomaly detection protocols inspired by those observed naturally in colonies of social insects to provide appropriate, dynamic, detection thresholds for anomalous event patterns on computer system networks to improve early detection and rejection methods to counter malicious threats.