research-article

An Intrusion Detection Feature Selection Method Based on Improved Fireworks Algorithm

Authors:

Shuangyue Niu,

Xiang Ji,

Jingmei Li,

Di Xue,

Weifei WuAuthors Info & Claims

ICCAI '20: Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence

Pages 356 - 361

https://doi.org/10.1145/3404555.3404556

Published: 20 August 2020 Publication History

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Abstract

With the rapid development of network technology, network intrusion has become increasingly frequent. In network intrusion detection technology, how to reduce feature dimensions and reduce redundant information is the key to improve the detection accuracy. To solve this problem, this paper proposes a new feature selection method SIFWA for intrusion detection based on improved fireworks algorithm. SIFWA optimized and improved the selection strategy of fireworks algorithm, which adopted the selection strategy based on fitness value to screen the next generation of fireworks, which could greatly improve the ability of fireworks algorithm to find the optimal solution and search efficiency to select more effective features for intrusion detection. Simulation experiments were conducted using UCI data. Simulation results show that SIFWA has higher detection accuracy than the benchmark algorithm.

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Jie XGaofeng LJun J(2021)Research on Solving Method of WTA Problem based on Firework Algorithm2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)10.1109/AEMCSE51986.2021.00091(406-411)Online publication date: Mar-2021
https://doi.org/10.1109/AEMCSE51986.2021.00091

Index Terms

An Intrusion Detection Feature Selection Method Based on Improved Fireworks Algorithm
1. Security and privacy
  1. Systems security
    1. Operating systems security
      1. Virtualization and security

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ICCAI '20: Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence

April 2020

563 pages

ISBN:9781450377089

DOI:10.1145/3404555

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. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Tsukuba: University of Tsukuba

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Association for Computing Machinery

New York, NY, United States

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Published: 20 August 2020

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ICCAI '20: 2020 6th International Conference on Computing and Artificial Intelligence

April 23 - 26, 2020

Tianjin, China

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Jie XGaofeng LJun J(2021)Research on Solving Method of WTA Problem based on Firework Algorithm2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)10.1109/AEMCSE51986.2021.00091(406-411)Online publication date: Mar-2021
https://doi.org/10.1109/AEMCSE51986.2021.00091

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A Two-step Feature Selection Algorithm Adapting to Intrusion Detection

An effective genetic algorithm-based feature selection method for intrusion detection systems

A comparison of feature-selection methods for intrusion detection

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