Art

J-GLOBAL ID：202102266611432174   Reference number：21A0993454

CNN-Based Network Intrusion Detection against Denial-of-Service Attacks

サービス拒否攻撃に対するCNNベースネットワーク侵入検出【JST・京大機械翻訳】

Author (5)： Kim Jiyeon (Center for Software Educational Innovation, Seoul Women’s University, Seoul 01797, Korea) ,  Kim Jiwon (Department of Information Security, Seoul Women’s University, Seoul 01797, Korea) ,  Kim Hyunjung (Department of Information Security, Seoul Women’s University, Seoul 01797, Korea) ,  Shim Minsun (Department of Information Security, Seoul Women’s University, Seoul 01797, Korea) ,  Choi Eunjung (Department of Information Security, Seoul Women’s University, Seoul 01797, Korea)
Material： Electronics (Web)
Volume： 9  Issue： 6  Page： 916  Publication year： 2020 
JST Material Number： U7178A  ISSN： 2079-9292  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： As cyberattacks become more in...

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Thesaurus term： health care ,  *machine learning
Semi thesaurus term： 防衛 ,  侵入検知システム ,  深層学習 ,  攻撃者 , 【Automatic Indexing@JST】

Author keywords (5)： intrusion detection systems ,  denial of service ,  deep learning ,  convolutional neural network ,  recurrent neural network

JST classification (2)： Data protection  (JD01020V) ,  Computer networks  (JC03000K)

Reference (58)：

• KDD. KDD CUP. Available online: https://kdd.ics.uci.edu/databases/kddcup99/task.html (accessed on 17 March 2020). Özgür, A.; Erdem, H. A review of KDD99 dataset usage in intrusion detection and machine learning between 2010 and 2015. Peer. J. Preprints 2016, 4, e1954v1.
• Paliwal, S.; Gupta, R. Denial-of-service, probing & remote to user (R2L) attack detection using genetic algorithm. Int. J. Comput. Appl. 2012, 60, 57-62.
• Shiravi, A.; Shiravi, H.; Tavallaee, M.; Ghorbani, A.A. Toward developing a systematic approach to generate benchmark datasets for intrusion detection. Comput. Secur. 2012, 31, 357-374.
• Anwar, S.; Mohamad Zain, J.; Zolkipli, M.; Inayat, Z.; Khan, S.; Anthony, B., Jr.; Chang, V. From intrusion detection to an intrusion response system: Fundamentals, requirements, and future directions. Algorithms 2017, 10, 39.
• Jing-Xin, W.; Zhi-Ying, W.; Kui, D. A network intrusion detection system based on the artificial neural networks. In Proceedings of the 3rd international conference on Information security, Shanghai, China, 14-16 November 2004; pp. 166-170.

Terms in the title (3)： サービス拒否攻撃 ,  CNN ,  侵入