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Distributed Wireless Intrusion Detection System
|關鍵字:||wireless local area network|
wireless access point
distributed wireless intrusion detection system
|引用:|| 郭彥鋒，”一個植基於異常資料串流挖掘的網路入侵偵測系統實作，”國立中興大學資訊科學系，June 2006. 李勁頤、陳奕明，“分散式入侵偵測系統研究現況介紹，” 國立中央大學資訊管理學系，Communication of the CCISA. Vol.8 No.2, March 2002.  A. L. N. Fred, "Data clustering using evidence accumulation," Pattern Recognition, 2002. Proceedings. 16th International Conference on, vol. 4, pp. 276-280 vol.4, 2002.  F. Weng, "An Intrusion Detection System Based on the Clustering Ensemble," Anti-Counterfeiting, Security, Identification, 2007 IEEE International Workshop on, pp. 121-124, 2007.  N. Wu, "An Outlier Mining-Based Method for Anomaly Detection," Anti-Counterfeiting, Security, Identification, 2007 IEEE International Workshop on, pp. 152-156, 2007.  R. Moskovitch, "Host Based Intrusion Detection using Machine Learning," Intelligence and Security Informatics, 2007 IEEE, pp. 107-114, 2007.  F. Gharibian, "Comparative Study of Supervised Machine Learning Techniques for Intrusion Detection," Communication Networks and Services Research, 2007. CNSR ''07. 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Sinha, "Wireless intrusion protection system using distributed collaborative intelligence," Performance, Computing, and Communications Conference, 2006. IPCCC 2006. 25th IEEE International, pp. 10 pp., 2006.  R. Bace and P. Mell, "Intrusion Detection System," National Institute of Standards and Technology (NIST) Special Publication on Intrusion Detection System.  D. E. Denning, "An Intrusion-Detection Model," Transactions on Software Engineering, vol. SE-13, pp. 222-232, 1987.  Z. Li, "Theoretical basis for intrusion detection," Information Assurance Workshop, 2005. IAW ''05. Proceedings from the Sixth Annual IEEE SMC, pp. 184-192, 2005.  Y.F. Zhang, "Distributed intrusion detection based on clustering," Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on, vol. 4, pp. 2379-2383 Vol. 4, 2005.  L. Vokorokos, "Security of distributed intrusion detection system based on multisensor fusion," Applied Machine Intelligence and Informatics, 2008. 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Chiueh, "Sequence Number- Based MAC Address Spoof Detection," In Proc. of 8th International Symposium on Recent Advances in Intrusion Detection (RAID 2005)  http://www.cert.org/  http://www.isaac.cs.berkeley.edu/isaac/wep-faq.html  http://oleg.wl500g.info/  http://www.dd-wrt.com/  http://openwrt.org/  http://snort-wireless.org/  http://www.kismetwireless.net/  http://www.ll.mit.edu/mission/communications/ist/corpora/ideval/docs/attackDB.html|
|摘要:||本論文有別於傳統經由有線(wired)網路而入侵的舊有的入侵偵測系統；我們所建立的無線網路入侵偵測系統，是為了偵測入侵者透過無線的環境，經由無線存取點而入侵到區域網路(Local Area Network，簡稱LAN)，因此我們透過實際去更改無線存取點(Access Point, AP)韌體的技術，將AP視為偵測入侵的感測器(sensor)，且將偵測重點放在目前最廣為大家所使用的802.11標準的無線區域網路。本論文提出一個結合集中與分散架構優點之分散式無線網路入侵偵測系統，藉由多個AP取得資料、分析資料後，再將結果交由分散式入侵偵測協調者做進一步的分析控制。從系統實作與實驗結果顯示，本系統確實能有效偵測無線網路入侵行為。|
As the number of wireless local area networks (WLAN) that conform to the IEEE 802.11 standards grows in an unprecedented rate, the security threats from WLAN raise concerns not only from the users but also from network administrators. In this thesis, we propose a distributed wireless intrusion detection system (DWIDS) for 802.11 WLAN. The proposed system is a hybrid of distributed and centralized architecture. In wireless networks, intruders may attack WLAN via wireless access point (AP). Therefore, AP can be used as the distributed sensors for detecting intrusions in the first place. In order to do it, we modified the firmware of AP and installed Snort-wireless and Kismet on AP for collecting and analyzing data. The analyzed data from different APs are then sent to the DWIDS coordinator for further processing. The implementation and experimental results show that the proposed system indeed detects several types of intrusions from WLAN.
|Appears in Collections:||資訊科學與工程學系所|
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