Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Mimicry attacks on host-based intrusion detection systems
Proceedings of the 9th ACM conference on Computer and communications security
Hiding Intrusions: From the Abnormal to the Normal and Beyond
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
A Sense of Self for Unix Processes
SP '96 Proceedings of the 1996 IEEE Symposium on Security and Privacy
Operating system stability and security through process homeostasis
Operating system stability and security through process homeostasis
Snort - Lightweight Intrusion Detection for Networks
LISA '99 Proceedings of the 13th USENIX conference on System administration
On evolving buffer overflow attacks using genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Automating mimicry attacks using static binary analysis
SSYM'05 Proceedings of the 14th conference on USENIX Security Symposium - Volume 14
Mimicry Attacks Demystified: What Can Attackers Do to Evade Detection?
PST '08 Proceedings of the 2008 Sixth Annual Conference on Privacy, Security and Trust
Undermining an anomaly-based intrusion detection system using common exploits
RAID'02 Proceedings of the 5th international conference on Recent advances in intrusion detection
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This work focuses on testing anomaly detectors from the perspective of a Multi-objective Evolutionary Exploit Generator (EEG). Such a framework provides users of anomaly detection systems two capabilities. Firstly, no knowledge of protected data structures need to be assumed (i.e. the detector is a black-box), where the time, knowledge and availability of tools to perform such an analysis might not be generally available. Secondly, the evolved exploits are then able to demonstrate weaknesses in the ensuing detector parameterization. Therefore, the system administrator can identify the suitable parameters for the effective operation of the detector. EEG is employed against two second generation anomaly detectors, namely pH and pH with schema mask, on four UNIX applications in order to perform a vulnerability assessment and make a comparison between the two detectors.