Title :
Anomaly-based intrusion detection using distributed intelligent systems
Author_Institution :
Dept. of Eng., Public Policy Carnegie Mellon Univ., Pittsburgh, PA
Abstract :
Anomaly based intrusion detection suffers from the uncontrollability of the rate of false alarms (false positive). What one computer may not be able to accomplish (reliable detection of a new malware with small false positive) many networked intelligently may. This paper is a proof of concept of that idea based on simulation with real data analysis. It speculates on how such set-up could be made part of a large scale intelligent system.
Keywords :
invasive software; anomaly-based intrusion detection; distributed intelligent systems; false alarms; malware; Analytical models; Computational modeling; Computer network reliability; Computer networks; Databases; Detectors; Intelligent networks; Intelligent systems; Internet; Intrusion detection; anomaly; false positives; intrusion detection; majority rule gates; network of computers;
Conference_Titel :
Risks and Security of Internet and Systems, 2008. CRiSIS '08. Third International Conference on
Conference_Location :
Tozeur
Print_ISBN :
978-1-4244-3309-4
DOI :
10.1109/CRISIS.2008.4757462