Self-similarity based lightweight intrusion detection method for cloud computing

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

Volumn 6592 LNAI, Issue PART 2, 2011, Pages 353-362

  Kwon, Hyukmin ^a   Kim, Taesu ^a   Yu, Song Jin ^b   Kim, Huy Kang ^a  

^a Korea University   (South Korea)

^b Korea Maritime University   (South Korea)

Author keywords

Anomaly detection; Cloud computing; Information security; Intrusion detection; Lightweight; Self similarity

Indexed keywords

ANOMALY DETECTION; ANOMALY DETECTION METHODS; CLOUD SYSTEMS; COMPUTING SERVICES; COSINE SIMILARITY; DATA LEAKAGE; HIGH PERFORMANCE COMPUTING; INTERNAL ACTIVITY; INTRUSION DETECTION METHOD; INTRUSION DETECTION SYSTEMS; KEY SUCCESS FACTORS; LEARNING PROCESS; LIGHTWEIGHT; OPTIMAL TIME; SELF-SIMILARITIES; SYSTEM CALLS; SYSTEM PERFORMANCE DEGRADATION;

CLOUD COMPUTING; DATABASE SYSTEMS; INTRUSION DETECTION; SECURITY OF DATA;

COMPUTER SYSTEMS;

EID: 84872111291     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-20042-7_36     Document Type: Conference Paper

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