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What is Artificial Immune System

Handbook of Research on Information Security and Assurance
A relatively new class of metaheuristics that mimics aspects of the human immune system to solve computational problems. This method has shown particular promise for anomaly detection. Previous artificial immune systems have shown some similarities with evolutionary computation. This is because they focus on the adaptive immune system. More recent approaches have combined this with aspects of the innate immune system to create a second generation of artificial immune systems.
Published in Chapter:
An Immune-Inspired Approach to Anomaly Detection
Jamie Twycross (University of Nottingham, UK)
Copyright: © 2009 |Pages: 13
DOI: 10.4018/978-1-59904-855-0.ch010
Abstract
The immune system provides a rich metaphor for computer security: anomaly detection that works in nature should work for machines. However, early artificial immune system approaches for computer security had only limited success. Arguably, this was due to these artificial systems being based on too simplistic a view of the immune system. We present here a second generation artificial immune system for process anomaly detection. It improves on earlier systems by having different artificial cell types that process information. Following detailed information about how to build such second generation systems, we find that communication between cells types is key to performance. Through realistic testing and validation, we show that second generation artificial immune systems are capable of anomaly detection beyond generic system policies. The chapter concludes with a discussion and outline of the next steps in this exciting area of computer security.
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More Results
A Hardware Immune System for MC8051 IP Core
Inspired by several immunological principles, Artificial Immune Systems (AIS) emerged in the 1990s as a new branch of Computational Intelligence. Like artificial neural networks (ANNs), evolutionary algorithms (EAs), and cellular automata, AISs also try to extract ideas from the biological mechanisms in order to develop novel computational techniques for solving science and engineering problems. A number of AIS models are applied in areas like pattern recognition, fault detection, computer security, etc. Among various AIS models, negative selection, immune network and clonal selection are the most discussed models.
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Application of Artificial Intelligence Techniques to Handle the Uncertainty in the Chemical Process for Environmental Protection
Artificial immune systems (AIS) are a class of computationally intelligent systems inspired by the principles and processes of the vertebrate immune system.
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Bio-Inspired Algorithms in Bioinformatics I
Biologically inspired computer algorithms that can be applied to various domains, including fault detection, function optimization, and intrusion detection. Also called computer immune system.
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Artificial Immune Systems for Anomaly Detection
an algorithm based on the functionality of the vertebrate immune system.
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