Paper Abstract and Keywords |
Presentation |
2019-03-05 14:30
Proposal of real-time brute-force attack detection and blocking system using software switch Yusei Katsura, Hiroyuki Kimiyama, Tomoaki Tsutsumi, Naoki Yonezaki (Tokyo Denki Univ.), Junki Ichikawa (NTT), Mitsuru Maruyama (Kanagawa Instiute of Technology) NS2018-272 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Recently, both number and scale of cyber attacks by using a large scale BotNet are increasing year by year. The BotNet executes brute-force attacks to expand themselves. We consider that blocking these brute-force attacks as soon as finding them are necessary to decrease cyber attacks. Therefore, we research and develop a system to detect above attacks in real-time and block them instantaneously. In this paper, we explain implementation method for the attack detection by machine learning and blocking system using software switch. We also show results for a performance measurement and discussion about using machine learning for brute-force attack detection. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Brute-force attack / machine learning / software switch / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 465, NS2018-272, pp. 461-464, March 2019. |
Paper # |
NS2018-272 |
Date of Issue |
2019-02-25 (NS) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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NS2018-272 |
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