Van Canh Vu

Le Quy Don Technical University

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Tuan-Hao Hoang

Le Quy Don Technical University

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Le Quy Don Technical University

UNSW Sydney

Australian Defence Force Academy

University of Canberra

Seoul National University

Vietnam Military Medical University

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Detect Wi-Fi Network Attacks Using Parallel Genetic Programming

Van Canh Vu Tuan-Hao Hoang

Wi-Fi network have been widely used nowadays. However, Intrusion Detection System (IDS) researches on Wi-Fi network were few and difficult since there was no common dataset between researchers on this area. Recently, Kolias et al. [2] published a comprehensive Wi-Fi network dataset extracting from real Wi-Fi traces, which is called the AWID dataset. Gene programming has proven effective in detecting network attacks, but the processing time is quite slow. Today, the development of GPU technology for high-speed parallel processing, the study of parallel programming solutions is essential. In this paper, we examined the Parallel Genetic Programming (Karoo GP) [13] in wireless attack detection to improve detection rates and processing time. The experiments showed that the processing time of Karoo GP was significantly improved compared to standard GP.

Parallel processing

10.1109/kse.2018.8573378

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