DocumentCode :
2777769
Title :
A method to evaluate Web Services Anomaly Detection using Hidden Markov Models
Author :
Rahnavard, Gholamali ; Najjar, Meisam S A ; Taherifar, Somaye
Author_Institution :
Comput. Sci. Dept., New Mexico State Univ., Las Cruces, NM, USA
fYear :
2010
fDate :
5-8 Dec. 2010
Firstpage :
261
Lastpage :
265
Abstract :
In spite of the existence of security challenges to develop informational and servicing structures, web services are important for organizations. There are so many things done to compensate for their security shortcomings, including replacing security standards in their structure to provide defensive tools such as web services firewall. Due to the is attempting inefficiency of the current Intrusion Detection Systems (IDS) in recognizing web services attacks, current research to enhance these systems´ level of security for the web services´ activities. The efficiency of the prevalent Intrusion Detection System can be compared and assessed using different parameters. But these methods are inefficient in the area of web systems. In this article, according to the implemented chores in the area of anomaly detection in the web services, we are going to evaluate the efficiency of Hidden Markov Models as a being-used method in the Web Services Anomaly Detection (WSAD) groundwork. The assessments´ methods and results can be used as an efficient and important step in guaranteeing web services.
Keywords :
Web services; authorisation; hidden Markov models; Web services anomaly detection evaluation; Web services attack; Web services firewall; defensive tool; hidden Markov model; intrusion detection system; security standard; servicing structure; Hidden Markov models; Mathematical model; Measurement; Security; Simple object access protocol; Training; Anomaly Detection; Hidden Markov Models; Web Services Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-9054-7
Type :
conf
DOI :
10.1109/ICCAIE.2010.5735086
Filename :
5735086
Link To Document :
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