政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/111697

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 113648/144635 (79%)
Visitors : 51569465 Online Users : 791

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

政大機構典藏 > 商學院 > 資訊管理學系 > 會議論文 > Item 140.119/111697

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/111697

Title:	Network-traffic anomaly detection with incremental majority learning
Authors:	郁方 Huang, Shin-Ying Yu, Fang Tsaih, Rua-Huan Huang, Yennun 蔡瑞煌
Contributors:	資管系
Keywords:	Computer crime;Data mining;Mercury (metal);Neural networks;Statistical tests;Adaptive modeling;Changing environment;Data abstraction;Essential features;Incremental learning;Intrusion Detection Systems;Outlier Detection;Training and testing;Intrusion detection
Date:	2015
Issue Date:	2017-08-09 17:28:34 (UTC+8)
Abstract:	Detecting anomaly behavior in large network traffic data has presented a great challenge in designing effective intrusion detection systems. We propose an adaptive model to learn majority patterns under a dynamic changing environment. We first propose unsupervised learning on data abstraction to extract essential features of samples. We then adopt incremental majority learning with iterative evolutions on fitting envelopes to characterize the majority of samples within moving windows. A network traffic sample is considered an anomaly if its abstract feature falls on the outside of the fitting envelope. We justify the effectiveness of the presented approach against 150000+ traffic samples from the NSL-KDD dataset in training and testing, demonstrating positive promise in detecting network attacks by identifying samples that have abnormal features. © 2015 IEEE.
Relation:	Proceedings of the International Joint Conference on Neural Networks, 2015-September
Data Type:	conference
DOI 連結:	http://dx.doi.org/10.1109/IJCNN.2015.7280573
DOI:	10.1109/IJCNN.2015.7280573
Appears in Collections:	[資訊管理學系] 會議論文

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML2	590	View/Open

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

Loading...