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An Immunological Approach to Change Detection: Algorithms
 Analysis and Implications,” IEEE Symposium on Security and Privacy
, 1996
"... We present new results on a distributable changedetection method inspired by the natural immune system. A weakness in the original algorithm was the exponential cost of generating detectors. Two detectorgenerating algorithms are introduced which run in linear time. The algorithms are analyzed, heur ..."
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Cited by 147 (21 self)
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We present new results on a distributable changedetection method inspired by the natural immune system. A weakness in the original algorithm was the exponential cost of generating detectors. Two detectorgenerating algorithms are introduced which run in linear time. The algorithms are analyzed, heuristics are given for setting parameters based on the analysis, and the presence of holes in detector space is examined. The analysis provides a basis for assessing the practicality of the algorithms in specific settings, and some of the implications are discussed. 1.
Y.: A virus detection system based on artificial immune system
 In: 2009 International Conference on Computational Intelligence and Security
, 2009
"... Abstract—A virus detection system (VDS) based on artificial ..."
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Cited by 3 (0 self)
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Abstract—A virus detection system (VDS) based on artificial
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"... What makes a problem easy or hard for a genetic algorithm (GA)? This question has become increasingly important as people have tried to apply the GA to ever more diverse types of problems. Much previous work on this question has studied the relationship between GA performance and the structure of a ..."
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What makes a problem easy or hard for a genetic algorithm (GA)? This question has become increasingly important as people have tried to apply the GA to ever more diverse types of problems. Much previous work on this question has studied the relationship between GA performance and the structure of a given fitness function when it is is expressed as a Walsh polynomial. The work of Bethke, Goldberg, and others has produced certain theoretical results about this relationship. In this paper we review these theoretical results, and then discuss a number of seemingly anomalous experimental results reported by Tanese concerning the performance of the GA on a subclass of Walsh polynomials, some members of which were expected to be easy for the GA to optimize. Tanese found that the GA was poor at optimizing all functions in this subclass, that a partitioning of a single large population into a number of smaller independent populations seemed to improve performance, and that hillclimbing outperformed both the original and partitioned forms of the GA on these functions. These results seemed to contradict several commonly held expectations about GAs. We begin by reviewing schema processing in GAs. We then give an informal description of how Walsh analysis and Bethke’s WalshSchema transform relate to GA performance, and we discuss the relevance of this analysis for GA applications in optimization and machine learning. We then describe Tanese’s surprising results, examine them experimentally and theoretically, and propose and evaluate some explanations. These explanations lead to a more fundamental question about GAs: what are the features of problems that determine the likelihood of successful GA performance? 1.
An Immunological Approach to Change Detection: Algorithms, Analysis and Implications
"... We present new results on a distributable changedetection method inspired by the natural immune system. A weakness in the original algorithm was the exponential cost of generating detectors. Two detectorgenerating algorithms are introduced which run in linear time. The algorithms are analyzed, heur ..."
Abstract
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We present new results on a distributable changedetection method inspired by the natural immune system. A weakness in the original algorithm was the exponential cost of generating detectors. Two detectorgenerating algorithms are introduced which run in linear time. The algorithms are analyzed, heuristics are given for setting parameters based on the analysis, and the presence of holes in detector space is examined. The analysis provides a basis for assessing the practicality of the algorithms in specific settings, and some of the implications are discussed. 1.
An Immunological Approach to Change Detection: Algorithms, Analysis and Implications
"... We present new results on a distributable changedetection method inspired by the natural immune system. A weakness in the original algorithm was the exponential cost of generating detectors. Two detectorgenerating algorithms are introduced which run in linear time. The algorithms are analyzed, heur ..."
Abstract
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We present new results on a distributable changedetection method inspired by the natural immune system. A weakness in the original algorithm was the exponential cost of generating detectors. Two detectorgenerating algorithms are introduced which run in linear time. The algorithms are analyzed, heuristics are given for setting parameters based on the analysis, and the presence of holes in detector space is examined. The analysis provides a basis for assessing the practicality of the algorithms in specific settings, and some of the implications are discussed. 1.
An Immunological Approach to Change Detection: Algorithms, Analysis and Implications
"... We present new results on a distributable changedetection method inspired by the natural immune system. A weakness in the original algorithm was the exponential cost of generating detectors. Two detectorgenerating algorithms are introduced which run in linear time. The algorithms are analyzed, heur ..."
Abstract
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We present new results on a distributable changedetection method inspired by the natural immune system. A weakness in the original algorithm was the exponential cost of generating detectors. Two detectorgenerating algorithms are introduced which run in linear time. The algorithms are analyzed, heuristics are given for setting parameters based on the analysis, and the presence of holes in detector space is examined. The analysis provides a basis for assessing the practicality of the algorithms in specific settings, and some of the implications are discussed. 1.