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Volumn , Issue , 2010, Pages 200-203

Intrusion detection based on fuzzy association rules

Author keywords

Association rules; Data mining; Fuzzy association rules; Intrusion detection

Indexed keywords

COMPUTER NETWORK TECHNOLOGY; DATA MINING TECHNOLOGY; FALSE POSITIVE RATES; FUZZY ASSOCIATION RULE; INTRUSION DETECTION SYSTEMS; PARTITION METHODS; RAPID DEVELOPMENT; SHARP BOUNDARY PROBLEM; SMOOTH TRANSITIONS;

EID: 78651085983     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPTC.2010.28     Document Type: Conference Paper
Times cited : (7)

References (7)
  • 5
    • 0348132918 scopus 로고    scopus 로고
    • Mining fuzzy association rules in databases
    • C. Kuok, A. Fu, M. Wong, Mining fuzzy association rules in databases, SIGMOD Record 27 (1) (1998) 41-46.
    • (1998) SIGMOD Record , vol.27 , Issue.1 , pp. 41-46
    • Kuok, C.1    Fu, A.2    Wong, M.3
  • 7
    • 26844574201 scopus 로고    scopus 로고
    • Applying data mining to intrusion detection: The quest for automation, efficiency and credibility
    • Issue
    • Wenke Lee, Applying data mining to intrusion detection: the quest for automation, efficiency and credibility, ACM SIGKDD Explorations Newsletter,2002,Vol.4,Issue
    • (2002) ACM SIGKDD Explorations Newsletter , vol.4
    • Lee, W.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.