González, Fabio Ph.D. The University of Memphis. May 2003. A Study of Artificial Immune Systems Applied to Anomaly Detection. Major Professor: Dipankar Dasgupta, Ph.D. The main goal of this research is to examine and to improve the anomaly detection function of artificial immune systems, specifically the negative selection algorithm and other self/non-self recognition techniques. This research ...

In this paper, we review the bio-inspired Artificial Immune System (AIS) using two detection and selection mechanism known as negative selection and clonal selections. AIS mimic the behavior of natural immune system to find the unknown pattern that have not been seen by the system similar to what bodies would do in facing the microbial entities. We simulate the behavior of negative selection an...

School of Resource and Environment Science, Wuhan University, Wuhan, China, 430079 Telephone: +86 18986075093 Email: [email protected] School of Resource and Environment Science, Wuhan University, Wuhan, China, 430079 Telephone: +86 13871298058 Email: [email protected] School of Resource and Environment Science, Wuhan University, Wuhan, China, 430079 Telephone: +86 13487074270 Email: liudian...

The paper introduces a speed boosting extension to a novel induction of fuzzy rules from raw data using Artificial Immune System methods. The modified algorithm was experimentally proved to be several times faster than

There is a need for new metaphors from immunology to flourish the application areas of Artificial Immune Systems. A metaheuristic called Obesity Heuristic derived from advances in obesity treatment is proposed. The main forces of the algorithm are the generation omega-6 and omega-3 fatty acids. The algorithm works with Just-In-Time philosophy; by starting only when desired. A case study of data...

The Attacks done by Viruses, Worms, Hackers, etc. are a Network Security-Problem in many Organisations. Current Intrusion Detection Systems have significant Disadvantages, e.g. the need of plenty of Computational Power or the Local Installation. Therefore, we introduce a novel Framework for Network Security which is called SANA. SANA contains an artificial Immune System with artificial Cells wh...

This paper presents a new tool for supervised learning, modeled on resource limited Artificial Immune Systems. A supervised learning system, it is self-regulatory, efficient, and stable under a wide range of user-set parameters. Its performance is comparable to well-established classifiers on a variety of testbeds, including the iris data, the diabetes classification problem, the ionosphere pro...

Artificial Immune Systems have been successfully applied to a number of problem domains including fault tolerance and data mining, but have been shown to scale poorly when applied to computer intrusion detection despite the fact that the biological immune system is a very effective anomaly detector. This may be because AIS algorithms have previously been based on the adaptive immune system and ...

This paper shows the potential accomplishments of artificial immune systems (in particular, the negative selection algorithm) application to the problem of speaker recognition. Both the use of binary representation of original signal and that of its Fast Fourier Transform in a real-number representation are analysed. A number of experiments are performed on different datasets to examine the per...

................................................................................................................................... I Acknowledgements .............................................................................................................. V List of Publications ............................................................................................................... ...