Title :
Protocol anomaly detection based on string kernels
Author :
Zhao, Jing ; Huang, Houkuan ; Tian, ShengFeng ; Yin, Chuanhuan
Author_Institution :
Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ., Beijing, China
Abstract :
Kernels defined on vectors have been widely used in host-based intrusion detection. We propose a protocol anomaly detection model based on string kernels including high-order Markov kernel, all-length gap-weighted kernel, all-length-weighted kernel and its variation all-length-weighted once kernel. Experimental results show that these string kernels can hold state information of protocols well. Models proposed achieve a high detection rate.
Keywords :
Markov processes; security of data; transport protocols; all-length gap-weighted kernel; high-order Markov kernel; host-based intrusion detection; protocol anomaly detection; string kernels; Data mining; Intrusion detection; Kernel; Optical computing; Photonics; Power engineering and energy; Protocols; Support vector machines; Telecommunication traffic; Traffic control; protocol anomaly detection; string kernel; support vector machine;
Conference_Titel :
Optics Photonics and Energy Engineering (OPEE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5234-7
Electronic_ISBN :
978-1-4244-5236-1
DOI :
10.1109/OPEE.2010.5508146