Principles of a computer immune system
NSPW '97 Proceedings of the 1997 workshop on New security paradigms
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
CDIS: Towards a Computer Immune System for Detecting Network Intrusions
RAID '00 Proceedings of the 4th International Symposium on Recent Advances in Intrusion Detection
Coverage and Generalization in an Artificial Immune System
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm
Genetic Programming and Evolvable Machines
Architecture for an Artificial Immune System
Evolutionary Computation
Models for threat assessment in networks
Models for threat assessment in networks
A new classifier based on resource limited artificial immune systems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Towards a Classifying Artificial Immune System for Web Server Attacks
ICMLA '09 Proceedings of the 2009 International Conference on Machine Learning and Applications
MILA: multilevel immune learning algorithm
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
The effect of binary matching rules in negative selection
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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This work presents theWeb Classifying Immune System (WCIS) which is a prototype system to detect zero-day attacks against web servers by examining web server requests. WCIS is intended to work in conjunction with more traditional intrusion detection systems to detect new and emerging threats that are not detected by the traditional IDS database. WCIS is at its core an artificial immune system, but WCIS expands on the concept of artificial immune systems by adding a classifier for web server requests. This gives the system administrator more information about the nature of the detected threat which is not given by a traditional artificial immune system. This prototype system also seeks to improve the efficiency of an artificial immune system by employing back-end, batch processing so that WCIS can detect threats on higher capacity networks. This work shows that WCIS is able to achieve a high rate of accuracy at detecting and classifying attacks against web servers with very few false positives.