Feature Selection Using Particle Swarm Optimization in Intrusion Detection
نویسندگان
چکیده
منابع مشابه
Intrusion Feature Selection Algorithm Based on Particle Swarm Optimization
High-dimensional intrusion detection data concentration information redundancy results in lower processing velocity of intrusion detection algorithm. Accordingly, the current study proposes an intrusion feature selection algorithm based on particle swarm optimization (PSO). Analyzing the features of the relevance between network intrusion data allows the PSO algorithm to optimally search in a f...
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Considering the relevance among features, which filter-based feature selection method fails to deal with, a kind of hybrid quantum particle swarm optimization and support vector machines based network intrusion feature selection wrapper algorithm is put forward. The subset of features is represented using quantum superposition characteristic and probability representation, among which superposi...
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Intrusion detection is one of the challenging tasks in today’s networked world. It is necessary to formulate a new intrusion detection system, which can monitor the network to detect the malicious activities. The proposed work focuses the issues, namely accuracy and efficiency. One way to improve performance is to use a minimal number of features to define a model in a way that it can be used t...
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ژورنال
عنوان ژورنال: International Journal of Distributed Sensor Networks
سال: 2015
ISSN: 1550-1329,1550-1477
DOI: 10.1155/2015/806954