Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Mining in a data-flow environment: experience in network intrusion detection
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Anomaly Detection over Noisy Data using Learned Probability Distributions
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Snort - Lightweight Intrusion Detection for Networks
LISA '99 Proceedings of the 13th USENIX conference on System administration
Architecture for an Artificial Immune System
Evolutionary Computation
A nonself space approach to network anomaly detection
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
An artificial immune system architecture for computer securityapplications
IEEE Transactions on Evolutionary Computation
An immunity-based technique to characterize intrusions in computernetworks
IEEE Transactions on Evolutionary Computation
Rule extraction from trained adaptive neural networks using artificial immune systems
Expert Systems with Applications: An International Journal
ACS'08 Proceedings of the 8th conference on Applied computer scince
Soft Computing Techniques for Internet Backbone Traffic Anomaly Detection
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Extracting rules for classification problems: AIS based approach
Expert Systems with Applications: An International Journal
A cooperative immunological approach for detecting network anomaly
Applied Soft Computing
A study of nature-inspired methods for financial trend reversal detection
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
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The paper presents an architecture of an anomaly detection system based on the paradigm of artificial immune systems (AISs). Incoming network traffic data are considered by the system as signatures of potential attackers by mapping them into antigens of AISs either using some parameters of network traffic or headers of selected TCP/IP protocols. A number of methods of generation of antibodies (anomaly detectors) were implemented. The way of anomaly detection depends on the method of antibodies generation. The paper presents results of an experimental study performed with use of real data and shows how the performance of the anomaly detection system depends on traffic data coding and methods of generation of detectors.