A Fast Probing Detection Method using Hybrid Machine Learning Algorithms
Pages 375 - 376
Abstract
Recently, a malicious user breaks into the network and destroys the entire network. This attack starts from probing. In this paper, we propose a fast probing detection technique for intrusion detection. In the past, probing detection was performed by analyzing all collected traffic characteristics and by supervised learning. In the proposed method, a normal traffic is classified through unsupervised learning and intrusion detection for probing attack is not performed for that traffic. The supervised learning is performed on traffic that may be abnormal. So, through the simulation, we verify that the proposed method can reduce times than the conventional method.
References
[1]
Iftikhar Ahmad, Azween B Abdullah, and Abdullah S Alghamdi. 2009. Applica tion of artificial neural network in detection of probing attacks. In IEEE Sympos ium on Industrial Electronics & Applications. IEEE, Kuala Lumpur, Malaysia, 57--62.
[2]
Gholam Reza Zargar, and Peyman Kabiri. 2009. Identification of effective network features for probing attack detection. In First International Conference on Networked Digital Technologies(NDT '09). IEEE. Ostrava. Czech Republic.
[3]
Vitaly Shmatikov, and Ming-Hsiu Wang. Security against probe-response attacks in collaborative intrusion detection. In Proceedings of the 2007 workshop on Large scale attack defense(LSAD '07). Kyoto, Japan, 129--136.
[4]
N. Khamphakdee, Nunnapus Benjamas, Saiyan Saiyod. 2015. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining. Journal of ICT Research and Applications, 8, 3, 234--250 pages.
[5]
UCI. 2009. The 3rd International Knowledge Discovery and Data Mining Tools Competition. http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html.
Index Terms
- A Fast Probing Detection Method using Hybrid Machine Learning Algorithms
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Published In
July 2019
419 pages
ISBN:9781450367646
DOI:10.1145/3323679
Copyright © 2019 Owner/Author.
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 02 July 2019
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- Refereed limited
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Mobihoc '19
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Mobihoc '19: The Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing
July 2 - 5, 2019
Catania, Italy
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Overall Acceptance Rate 296 of 1,843 submissions, 16%
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