Canh Vu, V. and Hoang, T.-H. (2018) Detect Wi-Fi Network Attacks Using Parallel Genetic Programming. In: 10th International Conference on Knowledge and Systems Engineering, KSE 2018, 1 November 2018 through 3 November 2018.
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Abstract
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. © 2018 IEEE.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Divisions: | Faculties > Faculty of Information Technology |
| Identification Number: | 10.1109/KSE.2018.8573378 |
| Uncontrolled Keywords: | Computer crime; Genetic algorithms; Genetic programming; Intrusion detection; Network security; Parallel programming; Systems engineering; Wireless local area networks (WLAN); Attack detection; Detection rates; Intrusion Detection Systems; Network attack; Parallel processing; Processing time; Programming solutions; Wi Fi networks; Wi-Fi |
| Additional Information: | Conference code: 143626. Language of original document: English. |
| URI: | http://eprints.lqdtu.edu.vn/id/eprint/9483 |
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