Title :
Application Layer Anomaly Detection Based on HSMM
Author :
Bailin, Xie ; Shunzheng, Yu ; Tao, Wang
Author_Institution :
Dept. of Electron. & Commun. Eng., Sun Yat-Sen Univ., Guangzhou, China
Abstract :
Today more and more network-based attacks occur at application layer. Observed from the network layer and transport layer, these attacks may not contain significant malicious activities, and generate abnormal network traffic. However, traditional security techniques usually detect attacks from those two layers. Although some security techniques can detect some application layer attacks, these techniques can only detect some known attacks, and these techniques can´t detect the unknown or novel attacks happened on application layer. In theory, application layer anomaly detection can detect the unknown and novel attacks happened on application layer, so the research of application layer anomaly detection is very important. This paper presents a new application layer anomaly detection method which based on HSMM. The experimental results show that this method has high detection accuracy and low false positive ratio.
Keywords :
Markov processes; computer network security; HSMM; application layer anomaly detection; hidden semiMarkov model; network layer; network-based attacks; transport layer; Hidden Markov models; Internet; Intrusion detection; Payloads; Protocols; Training; HSMM; anomaly detection; application layer; application layer attack; malicious activities;
Conference_Titel :
Information Technology and Applications (IFITA), 2010 International Forum on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-7621-3
Electronic_ISBN :
978-1-4244-7622-0
DOI :
10.1109/IFITA.2010.145