Another fuzzy anomaly detection system based on ant clustering algorithm

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

Volumn E100A, Issue 1, 2017, Pages 176-183

  Aminanto, Muhamad Erza ^a   Kim, Hakju ^a   Kim, Kyung Min ^a   Kim, Kwangjo ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

Ant clustering algorithm; Fuzzy logic; Unknown attacks; Unsupervised learning

Indexed keywords

COMPUTER CRIME; FUZZY LOGIC; INTRUSION DETECTION; LEARNING ALGORITHMS; PATTERN MATCHING; SIGNAL DETECTION; UNSUPERVISED LEARNING;

ANOMALY DETECTION SYSTEMS; ANT CLUSTERING ALGORITHM; CLASSIFICATION PROCESS; DISTANCE-BASED METHODS; FALSE POSITIVE RATES; INTRUSION DETECTION SYSTEMS; SIGNATURE DATABASE; UNKNOWN ATTACKS;

CLUSTERING ALGORITHMS;

EID: 85008343612     PISSN: 09168508     EISSN: 17451337     Source Type: Journal    
DOI: 10.1587/transfun.E100.A.176     Document Type: Conference Paper

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