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Data mining-based intrusion detectors: an overview of the columbia IDS project

Published: 01 December 2001 Publication History
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References

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1. Wenke Lee and Dong Xiang, Information-Theoretic Measures for Anomaly Detection, The 2001 IEEE Symposium on Security and Privacy, Oakland, CA, May 2001.]]
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2. J. B. D. Cabrera, L. Lewis, X. Qin, Wenke Lee, Ravi Prasanth, B. Ravichandran, and Raman Mehra, Proactive Detection of Distributed Denial of Service Attacks Using MIB Traffic Variables - A Feasibility Study, The Seventh IFIP/IEEE International Symposium on Integrated Network Management (IM 2001), Seattle, WA, May 2001.]]
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3. Wenke Lee, Rahul Nimbalkar, Kam Yee, Sunil Patil, Pragnesh Desai, Thuan Tran, and Sal Stolfo, A Data Mining and CIDF Based Approach for Detecting Novel and Distributed Intrusions In Proceedings of The Third International Workshop on Recent Advances in Intrusion Detection (RAID 2000), Lecture Notes in Computer Science No. 1907, Toulouse, France, October 2000.]]
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4. Eleazar Eskin, Wenke Lee and Salvatore J. Stolfo. "Modeling System Calls for Intrusion Detection with Dynamic Window Sizes." Proceedings of DISCEX II. June 2001.]]
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5. Wenke Lee, Salvatore J. Stolfo, Philip K. Chan, Eleazar Eskin, Wei Fan, Matthew Miller, Shlomo Hershkop and Junxin Zhang. "Real Time Data Mining-based Intrusion Detection.", Proceedings of DISCEX II. June 2001.]]
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6. Matthew G. Schultz, Eleazar Eskin, and Salvatore J. Stolfo. "Malicious Email Filter - A UNIX Mail Filter that Detects Malicious Windows Executables." Proceedings of USENIX Annual Technical Conference - FREENIX Track. Boston, MA: June 2001.]]
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7. Matthew G. Schultz, Eleazar Eskin, Erez Zadok, and Salvatore J. Stolfo. "Data Mining Methods for Detection of New Malicious Executables" Proceedings of IEEE Symposium on Security and Privacy. Oakland, CA: May 2001.]]
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8. Leonid Portnoy. "Intrusion Detection with Unlabeled Data using Clustering" Undergraduate Thesis. Columbia University: December, 2000.]]
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9. Eleazar Eskin, Matthew Miller, Zhi-Da Zhong, George Yi, Wei-Ang Lee, Sal Stolfo. "Adaptive Model Generation for Intrusion Detection Systems" Workshop on Intrusion Detection and Prevention, 7th ACM Conference on Computer Security, Athens, GR: November, 2000.]]
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10. Wenke Lee, Wei Fan, Matthew Miller, Sal Stolfo, and Erez Zadok. "Toward Cost-Sensitive Modeling for Intrusion Detection and Response" Workshop on Intrusion Detection and Prevention, 7th ACM Conference on Computer Security, Athens, GR: November, 2000.]]
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11. Eskin, Eleazar. "Anomaly Detection over Noisy Data using Learned Probability Distributions" ICML00, Palo Alto, CA: July, 2000.]]
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12. Wei Fan, Wenke Lee, Sal Stolfo, and Matthew Miller. "A Multiple Model Cost-Sensitive Approach for Intrusion Detection", Eleventh European Conference on Machine Learning (ECML '00) 2000.]]
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13. Sal Stolfo, Wei Fan, Wenke Lee, Andreas Prodromidis, and Phil Chan. "Cost-based Modeling for Fraud and Intrusion Detection: Results from the JAM Project" In Proceedings of the 2000 DARPA Information Survivability Conference and Exposition (DISCEX '00), 2000.]]
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14. Wenke Lee, Matthew Miller, Sal Stolfo, Kahil Jallad, Christoper Park, Erez Zadok, and Vijay Prabhakar. "Toward Cost-Sensitive Modeling for Intrusion Detection" Columbia University Computer Science Technical Report CUCS-002-00.]]
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15. Matthew Miller. "Learning Cost-Sensitive Classification Rules for Network Intrusion Detection using RIPPER" Columbia University Computer Science Technical Report CUCS-035-1999.]]
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16. Wenke Lee, Sal Stolfo, and Kui Mok. "Mining in a Data-flow Environment: Experience in Network Intrusion Detection" In Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD '99), San Diego, CA, August, 1999.]]
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17. Wenke Lee, Sal Stolfo, and Kui Mok. "A Data Mining Framework for Building Intrusion Detection Models" In Proceedings of the 1999 IEEE Symposium on Security and Privacy, Oakland, CA, May 1999.]]
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18. Wenke Lee, Chris Park, and Sal Stolfo. "Towards Automatic Intrusion Detection using NFR" In Proceedings of the 1st USENIX Workshop on Intrusion Detection and Network Monitoring, April 1999.]]
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19. Wenke Lee, Sal Stolfo, and Kui Mok. "Mining Audit Data to Build Intrusion Detection Models", In Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD '98), New York, NY, August 1998.]]
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20. Wenke Lee and Sal Stolfo. "Data Mining Approaches for Intrusion Detection" In Proceedings of the Seventh USENIX Security Symposium (SECURITY '98), San Antonio, TX, January 1998.]]
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21. Wenke Lee, Sal Stolfo, and Phil Chan. "Learning Patterns from Unix Process Execution Traces for Intrusion Detection", AAAI Workshop: Al Approaches to Fraud Detection and Risk Management, July 1997.]]
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1. Cost Complexity-based Pruning of Ensemble Classifiers, (with A. Prodromidis), Journal on Distributed and Parallel KDD, Special Issue on Knowledge and Information Systems, 2000.]]
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2. A Framework for Constructing Features and Models for Intrusion Detection Systems, (with W. Lee), ACM Transactions on Information and System Security, TISSEC, Vol 3, No. 4, November, 2000.]]
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3. Distributed Data Mining in Credit Card Fraud Detection, (with P. Chan, W. Fan, A. Prodromidis), IEEE Intelligent Systems, Vol. 14, No. 6, 1999.]]
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4. Adaptive Intrusion Detection: a Data Mining Approach, (with W. Lee and K. Mok), Artificial Intelligence Review, Volume 14, No. 6, Kluwer Academic Publishers, 2000, pp. 533-567.]]
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5. Wenke Lee, Wei Fan, Matthew Miller, Sal Stolfo, and Erez Zadok. "Toward Cost-Sensitive Modeling for Intrusion Detection and Response" Journal of Computer Security, (to appear), 2002.]]
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1. Philip Chan, An Extensible Meta-Learning Approach for Scalable and Accurate Inductive Learning, 1996. (Asst. Professor Florida Institute of Technology)]]
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2. Andreas Prodromidis, Efficiency and Scalability of Distributed Data Mining, Pruning and Bridging Multiple Models September 1999. (Director of Research iPrivacy LLC)]]
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3. Wenke Lee, A Data Mining Framework for Constructing Features and Models for Intrusion Detection Systems, June, 1999. (Asst. Professor, Georgia Tech).]]
[30]
4. Dave (Wei) Fan, Cost-sensitive, Scaleable AdaptiveLlearning. May 2001, (Member of the research staff at IBM research)]]

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Published In

cover image ACM SIGMOD Record
ACM SIGMOD Record  Volume 30, Issue 4
December 2001
104 pages
ISSN:0163-5808
DOI:10.1145/604264
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 December 2001
Published in SIGMOD Volume 30, Issue 4

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