Real-time diagnosis of network anomaly based on statistical traffic analysis

Proc. of the 11th IEEE Int. Conference on Trust, Security and Privacy in Computing and Communications, TrustCom-2012 - 11th IEEE Int. Conference on Ubiquitous Computing and Communications, IUCC-2012

Volumn , Issue , 2012, Pages 264-270

  Liu, Lei ^a   Jin, Xiaolong ^b   Min, Geyong ^c   Xu, Li ^d  

^a SHANDONG UNIVERSITY   (China)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^c UNIVERSITY OF BRADFORD   (United Kingdom)

^d FUJIAN NORMAL UNIVERSITY   (China)

Author keywords

Anomaly diagnosis; DDoS attack; Intrusion detection; Traffic measurement

Indexed keywords

BURSTY TRAFFIC; DATA SETS; DDOS ATTACK; DISTRIBUTED DENIAL OF SERVICE ATTACK; DOS ATTACKS; HURST PARAMETER; LINCOLN LABORATORY; NETWORK ANOMALIES; NETWORK SERVICE PROVIDERS; NETWORK TRAFFIC; NETWORK USERS; PERFORMANCE METRICS; REAL-TIME DIAGNOSIS; RESPOND TIME; SECOND GROUP; SELF-SIMILAR; SIMULATION EXPERIMENTS; TRAFFIC ANALYSIS; TRAFFIC ANOMALIES; TRAFFIC MEASUREMENTS;

EXPERIMENTS; INTRUSION DETECTION; UBIQUITOUS COMPUTING;

COMPUTER NETWORKS;

EID: 84868122550     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/TrustCom.2012.233     Document Type: Conference Paper

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