NDLI: P2P-AIS: A P2P Artificial Immune Systems architecture for detecting DDoS flooding attacks

Content Provider	IEEE Xplore Digital Library
Author	Ali, K. Aib, I. Boutaba, R.
Copyright Year	2009
Description	Author affiliation: David R. Cheriton School of Computer Science, University of Waterloo, Ontario, Canada (Ali, K.; Aib, I.; Boutaba, R.)
Abstract	The Human Immune System (HIS) plays an important role in protecting the human body from various intruders ranging from naive germs to the most sophisticated viruses. It acts as an Intrusion Detection and Prevention System (IDPS) for the human body and detects anomalies that make the body deviate from its normal behavior. This inspired researchers to build Artificial Immune Systems (AISes) which imitate the behavior of the HIS and are capable of protecting hosts or networks from attacks. An Artificial Immune System (AIS) is capable of detecting novel attacks because it is trained to differentiate between the normal behavior (self) and the abnormal behavior (non-self) during a tolerization (i.e training) period. Although several AISes have been proposed, only a few make use of collaborative approaches. In this paper we propose P2P-AIS, a P2P approach for AISes in which peers exchange intrusion detection experience in order to enhance attack detection and mitigation. P2P-AIS implements Chord as a distributed hash table (DHT) protocol to organize the peers.
Starting Page	1
Ending Page	4
File Size	292003
Page Count	4
File Format	PDF
ISBN	9781424446230
DOI	10.1109/GIIS.2009.5307053
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-23
Publisher Place	Tunisia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Protocols Humans intrusion detection distributed denial of service Floods Computer crime artificial immune systems Computer science peer-to-peer systems Artificial immune systems Intrusion detection Broadcasting Error correction Protection
Content Type	Text
Resource Type	Article

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