메뉴 건너뛰기




Volumn 1000, Issue 1, 2018, Pages

A Survey on Anomaly Based Host Intrusion Detection System

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER CRIME; NETWORK SECURITY; SURVEYS;

EID: 85046816278     PISSN: 17426588     EISSN: 17426596     Source Type: Conference Proceeding    
DOI: 10.1088/1742-6596/1000/1/012049     Document Type: Conference Paper
Times cited : (79)

References (36)
  • 4
    • 65249107163 scopus 로고    scopus 로고
    • A Simple and Efficient Hidden Markov Model Scheme for Host-Based Anomaly Intrusion Detection
    • Hu Jiankun and Yu Xinghuo 2009 A Simple and Efficient Hidden Markov Model Scheme for Host-Based Anomaly Intrusion Detection IEEE Network Journal 23
    • (2009) IEEE Network Journal , vol.23
    • Jiankun, H.1    Xinghuo, Y.2
  • 5
    • 85046713130 scopus 로고    scopus 로고
    • A Comprehensive Survey on Anomaly-Based Intrusion Detection in MANET
    • Kheyri Davood and Karami Mojtaba 2012 A Comprehensive Survey on Anomaly-Based Intrusion Detection in MANET Computer and Information Sciencevol. 5
    • (2012) Computer and Information Sciencevol. , vol.5
    • Davood, K.1    Mojtaba, K.2
  • 9
    • 84897137099 scopus 로고    scopus 로고
    • A semantic approach to host-based intrusion detection systems using contiguousanddiscontiguous system call patterns
    • Creech Gideon and Hu Jiankun 2014 A semantic approach to host-based intrusion detection systems using contiguousanddiscontiguous system call patterns IEEE Transactions on Computers 63 807-819
    • (2014) IEEE Transactions on Computers , vol.63 , Issue.4 , pp. 807-819
    • Gideon, C.1    Jiankun, H.2
  • 10
    • 85046765133 scopus 로고    scopus 로고
    • A multi-layer model for anomaly intrusion detection using program sequences of system calls
    • Hoang XuanDau, Hu Jiankun and Bertok Peter 2003 A multi-layer model for anomaly intrusion detection using program sequences of system calls In Proc. 11th IEEE Intl. Conf. Citeseer
    • (2003) Proc. 11th IEEE Intl. Conf. Citeseer
    • Xuandau, H.1    Jiankun, H.2    Peter, B.3
  • 15
    • 84941061963 scopus 로고    scopus 로고
    • Survey on Anomaly Detection using Data Mining Techniques
    • Agrawal Shikha and Agrawal Jitendra 2015 Survey on Anomaly Detection using Data Mining Techniques Procedia Computer Science 60 708-713
    • (2015) Procedia Computer Science , vol.60 , pp. 708-713
    • Shikha, A.1    Jitendra, A.2
  • 18
    • 33646423315 scopus 로고    scopus 로고
    • Application of anomaly detection algorithms for detecting SYN flooding attacks
    • Vasilios S and Fotini P 2006 Application of anomaly detection algorithms for detecting SYN flooding attacks Elsevier, Computer Communications 29 1433-1442
    • (2006) Elsevier, Computer Communications , vol.29 , Issue.9 , pp. 1433-1442
    • Vasilios, S.1    Fotini, P.2
  • 19
    • 36549085110 scopus 로고    scopus 로고
    • An active learning based TCMKNN algorithm for supervised network intrusiondetection
    • Yang Li and Li Guo 2007 An active learning based TCMKNN algorithm for supervised network intrusiondetection Elsevier, Computers & Security 459-467
    • (2007) Elsevier, Computers & Security , pp. 459-467
    • Li, Y.1    Guo, L.2
  • 20
    • 57849130705 scopus 로고    scopus 로고
    • Anomaly-based network intrusion detection: Techniques, systems and challenges
    • Garcia-Teodoro Pedro, Diaz-Verdejo J., Gabriel M and Enrique V 2009 Anomaly-based network intrusion detection: Techniques, systems and challenges computers& securityvol 28 18-28
    • (2009) Computers& Securityvol , vol.28 , Issue.1-2 , pp. 18-28
    • Pedro, G.1    Diaz-Verdejo, J.2    Gabriel, M.3    Enrique, V.4
  • 24
    • 19944364877 scopus 로고    scopus 로고
    • Feature deduction and ensemble design of intrusion detection systems
    • Chebrolu S., Abraham A. and Thomas J. P. 2005 Feature deduction and ensemble design of intrusion detection systems Comput. Secure. 24 295-307
    • (2005) Comput. Secure. , vol.24 , Issue.4 , pp. 295-307
    • Chebrolu, S.1    Abraham, A.2    Thomas, J.P.3
  • 25
    • 0033293396 scopus 로고    scopus 로고
    • Towards a Taxonomy of Intrusion Detection Systems
    • Herve D., Marc D. and Andreas W 1999 Towards a Taxonomy of Intrusion Detection Systems Elsevier, Computer Networks 31 805-822
    • (1999) Elsevier, Computer Networks , vol.31 , Issue.8 , pp. 805-822
    • Herve, D.1    Marc, D.2    Andreas, W.3
  • 28
    • 0035665469 scopus 로고    scopus 로고
    • A comparison of Intrusion Detection systems", Elsevier
    • Biermann Elmarie, Elsabe C. and Lucas V 2001 A comparison of Intrusion Detection systems", Elsevier Computers & Security 20 676-683
    • (2001) Computers & Security , vol.20 , Issue.8 , pp. 676-683
    • Elmarie, B.1    Elsabe, C.2    Lucas, V.3
  • 30
    • 84865209539 scopus 로고    scopus 로고
    • A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier
    • Koc Levent, Mazzuchi Thomas A. and Sarkani Shahram 2012 A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier Expert Systems with Applications 39 13492-500
    • (2012) Expert Systems with Applications , vol.39 , Issue.18 , pp. 13492-13500
    • Levent, K.1    Mazzuchi Thomas, A.2    Shahram, S.3
  • 31
    • 34250315640 scopus 로고    scopus 로고
    • An overview of anomaly detection techniques: Existing solutions and latest technological trends
    • Animesh P. and Jung-Min P 2007 An overview of anomaly detection techniques: Existing solutions and latest technological trends Elsevier, Science Direct, Computer Networks 51 3448-3470
    • (2007) Elsevier, Science Direct, Computer Networks , vol.51 , Issue.12 , pp. 3448-3470
    • Animesh, P.1    Jung-Min, P.2
  • 36
    • 85046791955 scopus 로고    scopus 로고
    • A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled dataIn
    • Eskin Eleazar, Andrew A., Michael P., Leonid P. and Sal S 2002 A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled dataIn D. Barbar and S.
    • (2002) D. Barbar and S.
    • Eleazar, E.1    Andrew, A.2    Michael, P.3    Leonid, P.4    Sal, S.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.