Anomaly intrusion detection for evolving data stream based on semi-supervised learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5506 LNCS, Issue PART 1, 2009, Pages 571-578

  Yu, Yan ^a   Guo, Shanqing ^b   Lan, Shaohua ^a   Ban, Tao ^c  

^a NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b SHANDONG UNIVERSITY   (China)

^c NATIONAL INSTITUTE OF INFORMATION AND COMMUNICATIONS TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ANOMALY INTRUSION DETECTION; ANOMALY-DETECTION ALGORITHMS; DATA SETS; DATA STREAM; DATA STREAM MODEL; DETECTION ACCURACY; DETECTION MODELS; HISTORICAL DATA; IN-NETWORK; LABELED DATA; SEMI-SUPERVISED LEARNING; TIME VARYING; TRAFFIC PATTERN; TRAIN DETECTION; TRAINING SAMPLE;

DATA COMMUNICATION SYSTEMS; DATA PROCESSING; LEARNING ALGORITHMS; SUPERVISED LEARNING; TIME VARYING NETWORKS;

INTRUSION DETECTION;

EID: 70349157637     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02490-0_70     Document Type: Conference Paper

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