A feasible intrusion detector for recognizing IIS attacks based on neural networks

Computers and Security

Volumn 27, Issue 3-4, 2008, Pages 84-100

  Horng, Shi Jinn ^a,b,c,d   Fan, Pingzhi ^a   Chou, Yao Ping ^b   Chang, Yen Cheng ^b   Pan, Yi ^d  

^a SOUTHWEST JIAOTONG UNIVERSITY   (China)

^b NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^c NATIONAL UNITED UNIVERSITY   (Taiwan)

^d GEORGIA STATE UNIVERSITY   (United States)

Author keywords

Back propagation neural network (BPN); Internet information services (IIS); Internet scanner system (ISS); Intrusion detection; Neural network

Indexed keywords

AEROSPACE ENGINEERING; ARTIFICIAL INTELLIGENCE; COMPUTER CRIME; INFORMATION SERVICES; INTERNET; NEURAL NETWORKS; SENSORS; SIGNAL DETECTION; STATISTICS; WEBSITES; WORLD WIDE WEB;

ABNORMAL DATA; BACK-PROPAGATION NEURAL NETWORK (BPN); DATA SETS; DETECTION RATES; EXPERIMENTAL DESIGN; FULL FACTORIAL; HYBRID INTRUSION DETECTION; INTERNET INFORMATION SERVICES; INTERNET INFORMATION SERVICES (IIS); INTERNET SCANNER SYSTEM (ISS); INTRUSION DETECTION SYSTEM; LOG FILES; NETWORK INTRUSIONS; NEURAL NETWORK; TAGUCHI; TRAINING DATA SETS; WEB SITE;

INTRUSION DETECTION;

EID: 49849084469     PISSN: 01674048     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cose.2008.04.004     Document Type: Article

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