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Volumn 31, Issue 1, 2008, Pages 58-72

Processing of massive audit data streams for real-time anomaly intrusion detection

Author keywords

Data streams; Hidden Markov models; Intrusion detection; Network security; Principal Component Analysis

Indexed keywords

COMPUTATIONAL EFFICIENCY; DATA REDUCTION; FEATURE EXTRACTION; HIDDEN MARKOV MODELS; NETWORK SECURITY; PRINCIPAL COMPONENT ANALYSIS;

EID: 37049002837     PISSN: 01403664     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.comcom.2007.10.010     Document Type: Article
Times cited : (79)

References (55)
  • 2
    • 0024122965 scopus 로고    scopus 로고
    • S.E. Smaha, Haystack: An intrusion detection system, in: Proceedings of the IEEE Fourth Aerospace Computer Security Applications Conference, 1988.
  • 3
    • 37049019603 scopus 로고    scopus 로고
    • T. Lunt, A. Tamaru, F. Gilham, R. Jagannathan, P. Neumann, H. Javitz, A. Valdes, T. Garvey, A real-time intrusion detection expert system (IDES) - final technical report, Technical report, Computer Science Laboratory, SRI International, Menlo Park, California, February 1992.
  • 4
    • 37049008609 scopus 로고    scopus 로고
    • D. Anderson, T. Frivold, A. Valdes, Next-generation intrusion detection expert system (NIDES): a summary. Technical Report SRI-CSL-95-07, Computer Science Laboratory, SRI International, Menlo Park, California, May 1995.
  • 5
    • 0034325396 scopus 로고    scopus 로고
    • Detecting masquerades in intrusion detection based on unpopular commands
    • Schonlau M., and Theus M. Detecting masquerades in intrusion detection based on unpopular commands. Information Processing Letters 76 (2000) 33-38
    • (2000) Information Processing Letters , vol.76 , pp. 33-38
    • Schonlau, M.1    Theus, M.2
  • 8
    • 0032218214 scopus 로고    scopus 로고
    • T. Lane, C.E. Brodley, Temporal sequence learning and data reduction for anomaly detection, in: Proceedings of Fifth ACM Conference on Computer and Communication Security, 1998.
  • 9
    • 35048851006 scopus 로고    scopus 로고
    • M.Oka, Y. Oyama, H. Abe, K. Kato, Anomaly detection using layered networks based on eigen co-occurrence matrix, in: Proceedings of Seventh International Symposium on Recent Advances in Intrusion Detection (RAID'2004), Springer, LNCS-3224, 2004, pp. 223-237.
  • 10
    • 0029716418 scopus 로고    scopus 로고
    • S. Forrest, S.A. Hofmeyr, A. Somayaji, T.A. Longstaff, A sense of self for Unix processes, in: Proceedings of the 1996 IEEE Symposium on Research in Security and Privacy, Los Alamos, CA, 1996, pp. 120-128.
  • 11
    • 85084163349 scopus 로고    scopus 로고
    • W. Lee, S. Stolfo, Data mining approaches for intrusion detection, in: Proceedings of the Seventh USENIX Security Symposium, Usenix Association, 1998, pp. 79-94.
  • 12
    • 84880174811 scopus 로고    scopus 로고
    • C. Warrender, S. Forrest, B. Pearlmutter, Detecting intrusions using system calls: alternative data models, in: Proceedings of 1999 IEEE Symposium on Security and Privacy, 1999, pp. 133-145.
  • 13
    • 0037142572 scopus 로고    scopus 로고
    • An anomaly intrusion detection method based on HMM
    • Yan Q., Xie W., Yan B., and Song G. An anomaly intrusion detection method based on HMM. Electronics Letters 38 13 (2002) 663-664
    • (2002) Electronics Letters , vol.38 , Issue.13 , pp. 663-664
    • Yan, Q.1    Xie, W.2    Yan, B.3    Song, G.4
  • 14
    • 0037209446 scopus 로고    scopus 로고
    • Host-based intrusion detection using dynamic and static behavioral models
    • Yeung D.Y., and Ding Y. Host-based intrusion detection using dynamic and static behavioral models. Pattern Recognition 36 1 (2003) 229-243
    • (2003) Pattern Recognition , vol.36 , Issue.1 , pp. 229-243
    • Yeung, D.Y.1    Ding, Y.2
  • 15
    • 0037282635 scopus 로고    scopus 로고
    • Efficient anomaly detection by modeling privilege flows using hidden Markov model
    • Cho S.B., and Park H.J. Efficient anomaly detection by modeling privilege flows using hidden Markov model. Computers and Security 22 1 (2003) 5-55
    • (2003) Computers and Security , vol.22 , Issue.1 , pp. 5-55
    • Cho, S.B.1    Park, H.J.2
  • 16
    • 6344239144 scopus 로고    scopus 로고
    • W. Wang, X. Guan, X. Zhang, Modeling program behaviors by hidden markov models for intrusion detection, in: Proceedings of the Third International Conference on Machine Learning and Cybernetics (ICMLC'2004), 2004, pp. 2830-2835.
  • 17
    • 37049019419 scopus 로고    scopus 로고
    • A. Wespi, M. Dacier, H. Debar, Intrusion detection using variable-length audit trail patterns, in: Proceedings of the Third International Workshop on the Recent Advances in Intrusion Detection (RAID'2000), LNCS-1907, 2000.
  • 19
    • 0034836392 scopus 로고    scopus 로고
    • W. Lee, D. Xiang, Information-theoretic measures for anomaly detection, in: Proceedings of the 2001 IEEE Symposium on Security and Privacy, Oakland, CA, May 2001.
  • 20
    • 0036321445 scopus 로고    scopus 로고
    • Use of k-nearest neighbor classifier for intrusion detection
    • Liao Y.H., and Vemuri V.R. Use of k-nearest neighbor classifier for intrusion detection. Computers and Security 21 5 (2002) 439-448
    • (2002) Computers and Security , vol.21 , Issue.5 , pp. 439-448
    • Liao, Y.H.1    Vemuri, V.R.2
  • 21
    • 37049018344 scopus 로고    scopus 로고
    • W. Hu, Y. Liao, V.R. Vemuri, Robust support vector machines for anomaly detection in computer security, in: Proceeding of the 2003 International Conference on Machine Learning and Applications (ICMLA'03), Los Angeles, California, 2003.
  • 22
    • 0036588773 scopus 로고    scopus 로고
    • Incorporating soft computing techniques into a probabilistic intrusion detection system
    • Cho S.B. Incorporating soft computing techniques into a probabilistic intrusion detection system. IEEE Transactions on Systems, Man, and Cybernetics - Part C 32 2 (2002) 154-160
    • (2002) IEEE Transactions on Systems, Man, and Cybernetics - Part C , vol.32 , Issue.2 , pp. 154-160
    • Cho, S.B.1
  • 23
    • 0242289557 scopus 로고    scopus 로고
    • A rough set theory based method for anomaly intrusion detection in computer networks
    • Cai Z., Guan X., Shao P., Peng Q., and Sun G. A rough set theory based method for anomaly intrusion detection in computer networks. Expert Systems 18 5 (2003) 251-259
    • (2003) Expert Systems , vol.18 , Issue.5 , pp. 251-259
    • Cai, Z.1    Guan, X.2    Shao, P.3    Peng, Q.4    Sun, G.5
  • 24
    • 2342576784 scopus 로고    scopus 로고
    • Predicting the intrusion intentions by observing system call sequences
    • Feng L., Guan X., Guo S., Gao Y., and Liu P. Predicting the intrusion intentions by observing system call sequences. Computers and Security 23 5 (2004) 241-252
    • (2004) Computers and Security , vol.23 , Issue.5 , pp. 241-252
    • Feng, L.1    Guan, X.2    Guo, S.3    Gao, Y.4    Liu, P.5
  • 25
    • 85128509431 scopus 로고    scopus 로고
    • W. Wang, X. Guan, X. Zhang, Profiling program and user behaviors for anomaly intrusion detection based on non-negative matrix factorization, in: Proceedings of 43rd IEEE Conference on Control and Decision (CDC'2004), Atlantis, Paradise Island, Bahamas, 2004, pp. 99-104.
  • 26
    • 1942436335 scopus 로고    scopus 로고
    • Robustness of the Markov chain model for cyber attack detection
    • Ye N., Zhang Y., and Borror C.M. Robustness of the Markov chain model for cyber attack detection. IEEE Transactions on Reliability 53 1 (2004) 116-121
    • (2004) IEEE Transactions on Reliability , vol.53 , Issue.1 , pp. 116-121
    • Ye, N.1    Zhang, Y.2    Borror, C.M.3
  • 27
    • 0035616570 scopus 로고    scopus 로고
    • A hybrid high-order Markov chain model for computer intrusion detection
    • Ju W.-H., and Vardi Y. A hybrid high-order Markov chain model for computer intrusion detection. Journal of Computational and Graphical Statistics 10 2 (2001) 277-295
    • (2001) Journal of Computational and Graphical Statistics , vol.10 , Issue.2 , pp. 277-295
    • Ju, W.-H.1    Vardi, Y.2
  • 28
    • 0037333205 scopus 로고    scopus 로고
    • Computer intrusion detection through EWMA for auto-correlated and uncorrelated data
    • Ye N., and Chen Q. Computer intrusion detection through EWMA for auto-correlated and uncorrelated data. IEEE Transactions on Reliability 52 1 (2003) 73-82
    • (2003) IEEE Transactions on Reliability , vol.52 , Issue.1 , pp. 73-82
    • Ye, N.1    Chen, Q.2
  • 30
    • 0035271352 scopus 로고    scopus 로고
    • An anomaly detection technique based on a chi-square statistic for detecting intrusions into information systems
    • Ye N., and Chen Q. An anomaly detection technique based on a chi-square statistic for detecting intrusions into information systems. Quality and Reliability Engineering International 17 2 (2001) 105-112
    • (2001) Quality and Reliability Engineering International , vol.17 , Issue.2 , pp. 105-112
    • Ye, N.1    Chen, Q.2
  • 31
    • 85042797742 scopus 로고    scopus 로고
    • A.K. Ghosh, A. Schwartzbard, M. Schatz, Learning program behavior profiles for intrusion detection, in: Proceedings of the First USENIX Workshop on Intrusion Detection and Network Monitoring, 1999, pp. 51-62.
  • 32
    • 37049020841 scopus 로고    scopus 로고
    • P.A. Porras, P.G. Neumann, EMERALD: Event Monitoring Enabling Responses to Anomalous Live Disturbances, in: Proceedings of National Information Systems Security Conference, Baltimore, MD, 1997.
  • 33
    • 0032676506 scopus 로고    scopus 로고
    • W. Lee, S. Stolfo, K. Mok, A data mining framework for adaptive intrusion detection, in: Proceedings of the 1999 IEEE Symposium on Security and Privacy, Los Alamos, CA, 1999, pp. 120-132.
  • 34
    • 84885774862 scopus 로고    scopus 로고
    • A Framework for constructing features and models for intrusion detection systems
    • Lee W., and Stolfo S. A Framework for constructing features and models for intrusion detection systems. ACM Transactions on Information and System Security 3 4 (2000) 227-261
    • (2000) ACM Transactions on Information and System Security , vol.3 , Issue.4 , pp. 227-261
    • Lee, W.1    Stolfo, S.2
  • 35
    • 1842712339 scopus 로고    scopus 로고
    • "A genetic clustering method for intrusion detection"
    • Liu Y., Chen K., Liao X., et al. "A genetic clustering method for intrusion detection". Pattern Recognition 37 5 (2004) 927-942
    • (2004) Pattern Recognition , vol.37 , Issue.5 , pp. 927-942
    • Liu, Y.1    Chen, K.2    Liao, X.3
  • 37
    • 37049012393 scopus 로고    scopus 로고
    • M. Shyu, S. Chen, K. Sarinnapakorn, L. Chang, A novel anomaly detection scheme based on principal component classifier, in: Proceedings of the IEEE Foundations and New Directions of Data Mining Workshop, in conjunction with the Third IEEE International Conference on Data Mining (ICDM'2003), 2003, pp. 172-179.
  • 38
    • 17544388668 scopus 로고    scopus 로고
    • H. Kayacik, A. Zincir-Heywood, M. Heywood, On the capability of an SOM based intrusion detection system, in: Proceedings of the IEEE International Joint Conference Neural Networks (IJCNN'2003), 2003, pp. 1808-1813.
  • 41
    • 0038330235 scopus 로고    scopus 로고
    • Fusion of multiple classifiers for intrusion detection in computer networks
    • Giacinto G., Roli F., and Didaci L. Fusion of multiple classifiers for intrusion detection in computer networks. Pattern Recognition Letters 24 5 (2003) 1795-1803
    • (2003) Pattern Recognition Letters , vol.24 , Issue.5 , pp. 1795-1803
    • Giacinto, G.1    Roli, F.2    Didaci, L.3
  • 42
    • 37049028483 scopus 로고    scopus 로고
    • MIT Lincoln Laboratory-DARPA Intrusion Detection Evaluation Documentation, , 1999.
  • 43
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • Rabiner L.R. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77 2 (1989)
    • (1989) Proceedings of the IEEE , vol.77 , Issue.2
    • Rabiner, L.R.1
  • 46
    • 36949094368 scopus 로고    scopus 로고
    • C. Kruegel, D. Mutz, F. Valeur and G. Vigna, On the detection of anomalous system call arguments, in: Eighth European Symposium on Research in Computer Security (ESORICS'2003), LNCS, Norway, 2003, pp. 101-118.
  • 48
    • 37049030130 scopus 로고    scopus 로고
    • CERT Advisory CA-2001-07 File, Globbing Vulnerabilities in Various FTP Servers, , 2001.
  • 52
    • 21144450811 scopus 로고    scopus 로고
    • W. Wang, X. Guan, X. Zhang, A novel intrusion detection method based on principal component analysis in computer security, in: Advances in Neural Networks-ISNN2004. International IEEE Symposium on Neural Networks, Dalian, China. LNCS-3174, August 2004, pp. 657-662.
  • 53
    • 33750949942 scopus 로고    scopus 로고
    • W. Wang, R. Battiti, Identifying intrusions in computer networks with principal component analysis, in: Proceedings of the First International Conference on Availability, Reliability and Security (ARES 2006), IEEE Press Society, Vienna, Austria, April 2006, pp. 270-277.
  • 54
    • 84880858814 scopus 로고    scopus 로고
    • K.M.C. Tan, R.A. Maxion, Why 6? Defining the operational limits of stide, an anomaly-based intrusion detector, in: Proceedings of 2002 IEEE Symposium on Security and Privacy, 2002, pp. 188- 201.
  • 55
    • 37049030131 scopus 로고    scopus 로고
    • KDD Cup 1999 Data, , 1999.


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