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Volumn 10, Issue 2, 2007, Pages 83-100

A multi-stage classification system for detecting intrusions in computer networks

Author keywords

Classification reliability; Intrusion detection systems; Multiple classifier systems; Network security; Reject option

Indexed keywords


EID: 34247625572     PISSN: 14337541     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10044-006-0053-7     Document Type: Article
Times cited : (14)

References (37)
  • 1
    • 0002067431 scopus 로고    scopus 로고
    • Netstat: A network based intrusion detection system
    • Vigna G, Kemmerer R (1999) Netstat: a network based intrusion detection system. J Comput Secur 7(1)
    • (1999) J Comput Secur , vol.7 , Issue.1
    • Vigna, G.1    Kemmerer, R.2
  • 2
    • 34247646917 scopus 로고    scopus 로고
    • Andersson S (1995) Detecting usual program behavior using the statistical component of the next-generation intrusion detection. Technical report, Comput Sci Lab
    • Andersson S (1995) Detecting usual program behavior using the statistical component of the next-generation intrusion detection. Technical report, Comput Sci Lab
  • 4
    • 0004309520 scopus 로고    scopus 로고
    • Research in intrusion detection systems: A survey
    • Chalmers University of Technology 98-17
    • Axelsson S (1999) Research in intrusion detection systems: a survey. Technical report TR, Chalmers University of Technology 98-17
    • (1999) Technical report TR
    • Axelsson, S.1
  • 6
    • 26444432211 scopus 로고    scopus 로고
    • Meier M, Schmerl S, Koenig H (2005) Improving the efficiency of misuse detection. In: Julisch K, Kruegel C (eds) LNCS 3548 Proceedings of the second international conference on detection of intrusions and malware, and vulnerability assessment, Vienna, Austria July 7-8, pp 188-205
    • Meier M, Schmerl S, Koenig H (2005) Improving the efficiency of misuse detection. In: Julisch K, Kruegel C (eds) LNCS vol. 3548 Proceedings of the second international conference on detection of intrusions and malware, and vulnerability assessment, Vienna, Austria July 7-8, pp 188-205
  • 7
    • 26944492141 scopus 로고    scopus 로고
    • Sy BK (2005) Signature-based approach for intrusion detection. In: Perner P, Imiya A (eds) LNAI 3587 In: Proceedings of the 4th international conference on machine learning and data mining in pattern recognition, Leipzig July 9-11
    • Sy BK (2005) Signature-based approach for intrusion detection. In: Perner P, Imiya A (eds) LNAI vol. 3587 In: Proceedings of the 4th international conference on machine learning and data mining in pattern recognition, Leipzig July 9-11
  • 8
    • 15944375471 scopus 로고    scopus 로고
    • Intrusion detection using hierarchical neural networks
    • Zhang C, Jiang J, Kamel M (2005) Intrusion detection using hierarchical neural networks. Pattern Recognit Lett 26(6):779-791
    • (2005) Pattern Recognit Lett , vol.26 , Issue.6 , pp. 779-791
    • Zhang, C.1    Jiang, J.2    Kamel, M.3
  • 10
    • 77949731575 scopus 로고    scopus 로고
    • Temporal sequence learning and data reduction for anomaly detection
    • Lane T, Brodley CE (1999) Temporal sequence learning and data reduction for anomaly detection. ACM Trans Inform System Secur 2(3):295-261
    • (1999) ACM Trans Inform System Secur , vol.2 , Issue.3 , pp. 295-261
    • Lane, T.1    Brodley, C.E.2
  • 11
    • 0141797880 scopus 로고    scopus 로고
    • A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled data
    • Barbara D, Jajodia S eds, Kluwer
    • Eskin E, Arnold A, Prerau M, Portnoy L, Stolfo S (2002) A geometric framework for unsupervised anomaly detection: detecting intrusions in unlabeled data. In: Barbara D, Jajodia S (eds) Applications of data mining in computer security, Kluwer
    • (2002) Applications of data mining in computer security
    • Eskin, E.1    Arnold, A.2    Prerau, M.3    Portnoy, L.4    Stolfo, S.5
  • 12
    • 0142126712 scopus 로고    scopus 로고
    • Novelty detection: A review-part 2: neural network based approaches
    • Singh S, Markou M (2003) Novelty detection: a review-part 2: neural network based approaches. Signal Process 83(12):2499-2521
    • (2003) Signal Process , vol.83 , Issue.12 , pp. 2499-2521
    • Singh, S.1    Markou, M.2
  • 13
    • 35248857893 scopus 로고    scopus 로고
    • Mahoney MV, Chan P (2003) An Analysis of the 1999 DARPA/Lincoln laboratory evaluation data for network anomaly detection. In: Vigna G, Jonsson E, Kruegel C (eds) LNCS 2820, Proceedings of RAID 2003, pp 220-238
    • Mahoney MV, Chan P (2003) An Analysis of the 1999 DARPA/Lincoln laboratory evaluation data for network anomaly detection. In: Vigna G, Jonsson E, Kruegel C (eds) LNCS vol. 2820, Proceedings of RAID 2003, pp 220-238
  • 14
    • 35248842651 scopus 로고    scopus 로고
    • Ramadas M, Ostermann S, Tjaden B (2003) Detecting anomalous network traffic with self-organizing maps. In: Vigna G, Jonsson E, Kruegel C (eds) LNCS 2820, Proceedings of RAID 2003, pp 36-54
    • Ramadas M, Ostermann S, Tjaden B (2003) Detecting anomalous network traffic with self-organizing maps. In: Vigna G, Jonsson E, Kruegel C (eds) LNCS vol. 2820, Proceedings of RAID 2003, pp 36-54
  • 15
    • 35048885009 scopus 로고    scopus 로고
    • Wang K, Stolfo SJ (2004) Anomalous payload-based network intrusion detection. In: Jonsson E, Valdes A, Almgren M (eds) LNCS, 3224, Proceedings of RAID 2004, pp 203-222
    • Wang K, Stolfo SJ (2004) Anomalous payload-based network intrusion detection. In: Jonsson E, Valdes A, Almgren M (eds) LNCS, vol. 3224, Proceedings of RAID 2004, pp 203-222
  • 18
    • 0038330235 scopus 로고    scopus 로고
    • Fusion of multiple classifiers for intrusion detection in computer networks
    • Giacinto G, Roli F, Didaci L (2003) Fusion of multiple classifiers for intrusion detection in computer networks. Pattern Recognit Lett 24:1795-1803
    • (2003) Pattern Recognit Lett , vol.24 , pp. 1795-1803
    • Giacinto, G.1    Roli, F.2    Didaci, L.3
  • 19
    • 0035402096 scopus 로고    scopus 로고
    • Training a neural network based intrusion detector to recognize novel attack
    • Lee SC, Heinbuch DV (2001) Training a neural network based intrusion detector to recognize novel attack. IEEE Trans Syst Man Cybern Part-A 31:294-299
    • (2001) IEEE Trans Syst Man Cybern , vol.31 , Issue.PART-A , pp. 294-299
    • Lee, S.C.1    Heinbuch, D.V.2
  • 20
    • 0038266786 scopus 로고    scopus 로고
    • Computer intrusion detection with classification and anomaly detection, using SVMs
    • Fugate M, Gattiker JR (2003) Computer intrusion detection with classification and anomaly detection, using SVMs. Intern J Pattern Recognit Artif Intell 17(3):441-458
    • (2003) Intern J Pattern Recognit Artif Intell , vol.17 , Issue.3 , pp. 441-458
    • Fugate, M.1    Gattiker, J.R.2
  • 21
    • 27244444099 scopus 로고    scopus 로고
    • A modular multiple classifier system for the detection of intrusions
    • Giacinto G, Roli F, Didaci L (2003) A modular multiple classifier system for the detection of intrusions. Lecture Notes Comput Sci 2709:346-355
    • (2003) Lecture Notes Comput Sci , vol.2709 , pp. 346-355
    • Giacinto, G.1    Roli, F.2    Didaci, L.3
  • 22
    • 0034347189 scopus 로고    scopus 로고
    • Signature verification: Increasing performance by a multi-stage system
    • Sansone C, Vento M (2000) Signature verification: increasing performance by a multi-stage system. Pattern Anal Appl 3(2):169-181
    • (2000) Pattern Anal Appl , vol.3 , Issue.2 , pp. 169-181
    • Sansone, C.1    Vento, M.2
  • 23
    • 0036716781 scopus 로고    scopus 로고
    • Cooperating experts for soundtrack analysis of MPEG movies
    • De Santo M, Percannella G, Sansone C, Vento M (2002) Cooperating experts for soundtrack analysis of MPEG movies. Inf Fusion 3(3):225-236
    • (2002) Inf Fusion , vol.3 , Issue.3 , pp. 225-236
    • De Santo, M.1    Percannella, G.2    Sansone, C.3    Vento, M.4
  • 24
    • 21144446383 scopus 로고    scopus 로고
    • An empirical comparison of hierarchical vs two level approaches to multiclass problems
    • Rajan S, Ghosh J (2004) An empirical comparison of hierarchical vs two level approaches to multiclass problems. Lecture Notes Comput Sci 3077:283-292
    • (2004) Lecture Notes Comput Sci , vol.3077 , pp. 283-292
    • Rajan, S.1    Ghosh, J.2
  • 28
    • 35048891979 scopus 로고    scopus 로고
    • Classifiers ensembles for changing environments
    • Kuncheva LI (2004) Classifiers ensembles for changing environments. Lecture Notes Comput Sci 3077:1-15
    • (2004) Lecture Notes Comput Sci , vol.3077 , pp. 1-15
    • Kuncheva, L.I.1
  • 30
    • 0033461670 scopus 로고    scopus 로고
    • Reliability parameters to improve combination strategies in multi-expert systems
    • Cordella LP, Foggia P, Sansone C, Tortorella F, Vento M (1999) Reliability parameters to improve combination strategies in multi-expert systems. Pattern Anal Appl 3(2):205-214
    • (1999) Pattern Anal Appl , vol.3 , Issue.2 , pp. 205-214
    • Cordella, L.P.1    Foggia, P.2    Sansone, C.3    Tortorella, F.4    Vento, M.5
  • 31
    • 0038428854 scopus 로고    scopus 로고
    • Results of the KDD99 classifier learning
    • Elkan C (2000) Results of the KDD99 classifier learning. ACM SIGKDD Explorations 1:63-64
    • (2000) ACM SIGKDD Explorations , vol.1 , pp. 63-64
    • Elkan, C.1
  • 32
    • 84885774862 scopus 로고    scopus 로고
    • A framework for constructing features and models for intrusion detection systems
    • Lee W, Stolfo SJ (2000) A framework for constructing features and models for intrusion detection systems. ACM Trans Inform System Secur 3(4):227-261
    • (2000) ACM Trans Inform System Secur , vol.3 , Issue.4 , pp. 227-261
    • Lee, W.1    Stolfo, S.J.2
  • 33
    • 85019691440 scopus 로고    scopus 로고
    • Testing intrusion detection systems: A critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by lincoln laboratory
    • McHugh J (2000) Testing intrusion detection systems: a critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by lincoln laboratory. ACM Trans Inform System Secur 3(4):262-294
    • (2000) ACM Trans Inform System Secur , vol.3 , Issue.4 , pp. 262-294
    • McHugh, J.1
  • 34
  • 36
    • 0034830461 scopus 로고    scopus 로고
    • Decision templates for multiple classifier fusion: An experimental comparison
    • Kuncheva LI, Bezdek JC, Duin RPW (2001) Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recognit 34(2):299-314
    • (2001) Pattern Recognit , vol.34 , Issue.2 , pp. 299-314
    • Kuncheva, L.I.1    Bezdek, J.C.2    Duin, R.P.W.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.