Using Genetic Algorithm for Network Intrusion Detection

By Wei Li. 2004

361 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/917554c7cce69e6ee9708020863f2bd27fa986a6

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Citations in the corpus

Anomaly-based network intrusion detection: Techniques, systems and challenges (2009, methodology): “Thus, genetic algorithms constitute another type of machine learning-based technique, capable of deriving classification rules (Li, 2004) and/or selecting appropriate features or optimal parameters for the detection process (Bridges and Vaughn, 2000).”
An Implementation of Intrusion Detection System Using Genetic Algorithm (2012, methodology): “Li [6] described a method using GA to detect anomalous network intrusion [19][20].”
Deep Learning Approach for Intelligent Intrusion Detection System (2019, methodology): “In [29], a genetic algorithm based NIDS was proposed that facilitates to model both temporal and spatial information to identify complex anomalous behavior.”
The use of computational intelligence in intrusion detection systems: A review (2010, methodology): “A “don’t care” symbol, ∗, is included [117, 159, 188, 189, 213, 222, 233, 248] as a wild card that allows any possible value in a gene,”
An overview of anomaly detection techniques: Existing solutions and latest technological trends (2007, methodology): “Some approaches [54,55] have used genetic algorithms directly to derive classification rules, while others [52,56] use genetic algorithms to select appropriate features or determine optimal parameters of related functions, while different data mining techniques are then used to acquire the rules.”
Decision tree classifier for network intrusion detection with GA-based feature selection (2005, background): “INTRODUCTION Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.”