Accession Number : AD1030768


Title :   Bio-Inspired Distributed Decision Algorithms for Anomaly Detection


Descriptive Note : Technical Report,01 Sep 2012,01 Sep 2016


Corporate Author : Rutgers University New Brunswick United States


Personal Author(s) : Fefferman,Nina H


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1030768.pdf


Report Date : 01 Mar 2017


Pagination or Media Count : 53


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.


Descriptors :   detection , computer networks , network topology , algorithms , computing system architectures


Subject Categories : Computer Systems


Distribution Statement : APPROVED FOR PUBLIC RELEASE