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Volumn 3, Issue , 2009, Pages 261-264

Network intrusion detection method based on improved simulated annealing neural network

Author keywords

Intrusion behaviors; Intrusion detection; Neural network; Simulated annealing algorithm

Indexed keywords

BP NETWORKS; FASTER CONVERGENCE; IMPACT FACTOR; INTRUSION BEHAVIORS; INTRUSION DETECTION METHOD; NETWORK INTRUSION DETECTION METHOD; NETWORK STRUCTURES; NETWORK WEIGHTS; POWELL ALGORITHMS; SELF-LEARNING; SIMULATED ANNEALING ALGORITHM; SIMULATED ANNEALING ALGORITHMS;

EID: 70449348670     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMTMA.2009.548     Document Type: Conference Paper
Times cited : (7)

References (9)
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  • 2
    • 66249136170 scopus 로고    scopus 로고
    • Research of intrusion detection based on neural network optimized by adaptive genetic algorithm
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    • (2008) Computer Engineering and Design , vol.29 , Issue.12 , pp. 3022-3025
    • Qinglin, L.1    Lu, H.2
  • 3
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    • Xian: Xi an electronic science and technology university press
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    • (1995) Neural network system theory
    • Licheng, J.1
  • 5
    • 0023669879 scopus 로고
    • Nonconvex Optimization by Fast Simulated Annealing
    • Harold H. Szu and Ralph L. Hartley, Nonconvex Optimization by Fast Simulated Annealing, Proceedings of the IEEE, vol. 75, no. 11, pp. 1538-1540, 1987.
    • (1987) Proceedings of the IEEE , vol.75 , Issue.11 , pp. 1538-1540
    • Szu, H.H.1    Hartley, R.L.2
  • 6
    • 4344659702 scopus 로고    scopus 로고
    • Anomaly detection methods in wired networks, A survey and taxonomy
    • Juan M E T, Pedro G T, Jesus E D V, et al, "Anomaly detection methods in wired networks", A survey and taxonomy, Computer Communications, vol. 27, no. 16, pp. 1569-1584, 2004.
    • (2004) Computer Communications , vol.27 , Issue.16 , pp. 1569-1584
    • Juan, M.E.T.1    Pedro, G.T.2    Jesus, E.D.V.3
  • 7
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    • Intrusion detection techniques and approaches
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    • Theuns, V.1    Ray, H.2
  • 8
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    • Lincoln Laboratory, Massachusetts Institute of Technology. DARPA intrusion detection evaluation[EB/OL]. http://www.11.mit.edu/IST/ideval/index. html, 2003-06-16.
    • Lincoln Laboratory, Massachusetts Institute of Technology. DARPA intrusion detection evaluation[EB/OL]. http://www.11.mit.edu/IST/ideval/index. html, 2003-06-16.
  • 9
    • 0037411435 scopus 로고    scopus 로고
    • The neural network models for IDS based on the asymmet ric cost s of false negative errors and false positive errors
    • JOO D, HON G T, HAN I, "The neural network models for IDS based on the asymmet ric cost s of false negative errors and false positive errors", Expert System with Applications, vol. 25, no. 1, pp. 69-75, 2003.
    • (2003) Expert System with Applications , vol.25 , Issue.1 , pp. 69-75
    • JOO, D.1    HON, G.T.2    HAN, I.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.