Mining in a data-flow environment

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Mining in a data-flow environment: experience in network intrusion detection

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International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents

San Diego, California, United States

Pages: 114 - 124

Year of Publication: 1999

ISBN:1-58113-143-7

Authors

Wenke Lee	Computer Science Department, Columbia University
Salvatore J. Stolfo	Computer Science Department, Columbia University
Kui W. Mok	Computer Science Department, Columbia University

Sponsors

SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
AAAI : Am Assoc for Artifical Intelligence
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 13, Downloads (12 Months): 92, Citation Count: 31

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY 31

	Jeffrey Vetter, Performance analysis of distributed applications using automatic classification of communication inefficiencies, Proceedings of the 14th international conference on Supercomputing, p.245-254, May 08-11, 2000, Santa Fe, New Mexico, United States
	Wenke Lee, Applying data mining to intrusion detection: the quest for automation, efficiency, and credibility, ACM SIGKDD Explorations Newsletter, v.4 n.2, p.35-42, December 2002
	Salvatore J. Stolfo , Wenke Lee , Philip K. Chan , Wei Fan , Eleazar Eskin, Data mining-based intrusion detectors: an overview of the columbia IDS project, ACM SIGMOD Record, v.30 n.4, December 2001
	Wenke Lee , Salvatore J. Stolfo, A framework for constructing features and models for intrusion detection systems, ACM Transactions on Information and System Security (TISSEC), v.3 n.4, p.227-261, Nov. 2000
	Kenji Yamanishi , Jun-Ichi Takeuchi , Graham Williams , Peter Milne, On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms, Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, p.320-324, August 20-23, 2000, Boston, Massachusetts, United States
	Wenke Lee , Salvatore J. Stolfo , Kui W. Mok, Algorithms for mining system audit data, Data mining, rough sets and granular computing, Physica-Verlag GmbH, Heidelberg, Germany, 2002
	Wenke Lee , Salvatore J. Stolfo , Kui W. Mok, Adaptive Intrusion Detection: A Data Mining Approach, Artificial Intelligence Review, v.14 n.6, p.533-567, December 1, 2000
	Christopher Kruegel , Giovanni Vigna, Anomaly detection of web-based attacks, Proceedings of the 10th ACM conference on Computer and communications security, October 27-30, 2003, Washington D.C., USA
	Stefano Zanero , Sergio M. Savaresi, Unsupervised learning techniques for an intrusion detection system, Proceedings of the 2004 ACM symposium on Applied computing, March 14-17, 2004, Nicosia, Cyprus
	Nong Ye , Syed Masum Emran , Qiang Chen , Sean Vilbert, Multivariate Statistical Analysis of Audit Trails for Host-Based Intrusion Detection, IEEE Transactions on Computers, v.51 n.7, p.810-820, July 2002
	Jun Li , Dejing Dou , Zhen Wu , Shiwoong Kim , Vikash Agarwal, An internet routing forensics framework for discovering rules of abnormal BGP events, ACM SIGCOMM Computer Communication Review, v.35 n.5, October 2005
	Angelos D. Keromytis , Janak Parekh , Philip N. Gross , Gail Kaiser , Vishal Misra , Jason Nieh , Dan Rubenstein , Sal Stolfo, A holistic approach to service survivability, Proceedings of the 2003 ACM workshop on Survivable and self-regenerative systems: in association with 10th ACM Conference on Computer and Communications Security, p.11-22, October 31-31, 2003, Fairfax, VA
	Wenke Lee , Wei Fan, Mining system audit data: opportunities and challenges, ACM SIGMOD Record, v.30 n.4, December 2001
	Philip K. Chan , Wei Fan , Andreas L. Prodromidis , Salvatore J. Stolfo, Distributed Data Mining in Credit Card Fraud Detection, IEEE Intelligent Systems, v.14 n.6, p.67-74, November 1999
	Xiao-Bai Li, A scalable decision tree system and its application in pattern recognition and intrusion detection, Decision Support Systems, v.41 n.1, p.112-130, November 2005
	Darren Mutz , Fredrik Valeur , Giovanni Vigna , Christopher Kruegel, Anomalous system call detection, ACM Transactions on Information and System Security (TISSEC), v.9 n.1, p.61-93, February 2006
	Yong Guo Liu , Xiao Feng Liao , Xue Ming Li , Zhong Fu Wu, A Tabu Clustering algorithm for Intrusion Detection, Intelligent Data Analysis, v.8 n.4, p.325-344, September 2004
	Maheshkumar Sabhnani , Gursel Serpen, Why machine learning algorithms fail in misuse detection on KDD intrusion detection data set, Intelligent Data Analysis, v.8 n.4, p.403-415, September 2004
	Franciszek Seredynski , Pascal Bouvry, Anomaly detection in TCP/IP networks using immune systems paradigm, Computer Communications, v.30 n.4, p.740-749, February, 2007
	Salvatore J. Stolfo , Shlomo Hershkop , Chia-Wei Hu , Wei-Jen Li , Olivier Nimeskern , Ke Wang, Behavior-based modeling and its application to Email analysis, ACM Transactions on Internet Technology (TOIT), v.6 n.2, p.187-221, May 2006
	Challa S. Sastry , Sanjay Rawat , Arun K. Pujari , V. P. Gulati, Network traffic analysis using singular value decomposition and multiscale transforms, Information Sciences: an International Journal, v.177 n.23, p.5275-5291, December, 2007
	Sirish Chandrasekaran , Michael J. Franklin, Streaming queries over streaming data, Proceedings of the 28th international conference on Very Large Data Bases, p.203-214, August 20-23, 2002, Hong Kong, China
	Salvatore J. Stolfo , Frank Apap , Eleazar Eskin , Katherine Heller , Shlomo Hershkop , Andrew Honig , Krysta Svore, A comparative evaluation of two algorithms for Windows Registry Anomaly Detection, Journal of Computer Security, v.13 n.4, p.659-693, July 2005
	Taghi M. Khoshgoftaar , Kehan Gao , Nawal H. Ibrahim, Evaluating indirect and direct classification techniques for network intrusion detection, Intelligent Data Analysis, v.9 n.3, p.309-326, May 2005
	Lih-Chyau Wuu , Chi-Hsiang Hung , Sout-Fong Chen, Building intrusion pattern miner for Snort network intrusion detection system, Journal of Systems and Software, v.80 n.10, p.1699-1715, October, 2007
	Sirish Chandrasekaran , Michael J. Franklin, PSoup: a system for streaming queries over streaming data, The VLDB Journal — The International Journal on Very Large Data Bases, v.12 n.2, p.140-156, August 2003
	Kenji Yamanishi , Jun-Ichi Takeuchi , Graham Williams , Peter Milne, On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms, Data Mining and Knowledge Discovery, v.8 n.3, p.275-300, May 2004
	Shao-Shin Hung , Damon Shing-Min Liu, A user-oriented ontology-based approach for network intrusion detection, Computer Standards & Interfaces, v.30 n.1-2, p.78-88, January, 2008
	Taghi M. Khoshgoftaar , Kehan Gao , Hua Lin, Indirect classification approaches: a comparative study in network intrusion detection, International Journal of Computer Applications in Technology, v.27 n.4, p.232-245, October 2006
	Tak-Chung Fu , Chung-Leung Lui, Agent-oriented network intrusion detection system using data mining approaches, International Journal of Agent-Oriented Software Engineering, v.1 n.2, p.158-174, July 2007
	Stephen F. Owens , Reuven R. Levary, An adaptive expert system approach for intrusion detection, International Journal of Security and Networks, v.1 n.3/4, p.206-217, December 2006