A fuzzy anomaly detection system based on hybrid PSO-Kmeans algorithm in content-centric networks

Neurocomputing

Volumn 149, Issue PC, 2015, Pages 1253-1269

  Karami, Amin ^a   Guerrero Zapata, Manel ^a  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

Anomaly detection; Clustering analysis; Content centric networks; Fuzzy set; K means; Particle swarm optimization

Indexed keywords

COST FUNCTIONS; DENIAL-OF-SERVICE ATTACK; FUZZY NEURAL NETWORKS; FUZZY SETS; K-MEANS CLUSTERING; NETWORK SECURITY; PARTICLE SWARM OPTIMIZATION (PSO);

ANOMALY DETECTION METHODS; ANOMALY DETECTION SYSTEMS; CLUSTERING ANALYSIS; CONTENT-CENTRIC NETWORKS; DISTANCE-BASED METHODS; FALSE POSITIVE RATES; K-MEANS; LOCAL OPTIMIZATIONS;

ANOMALY DETECTION;

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; COMPUTER NETWORK; COMPUTER PROGRAM; CONTENT CENTRIC NETWORK; FALSE POSITIVE RESULT; FUZZY SYSTEM; HYBRIDIZATION; INTERMETHOD COMPARISON; INTERNET; MATHEMATICAL MODEL; ONLINE SYSTEM; PARTICLE SWARM OPTIMIZATION; PROCESS MONITORING; VALIDATION PROCESS;

EID: 84912115872     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.08.070     Document Type: Article

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