Title :
Generating Attack Scenarios for Attack Intention Recognition
Author :
Feng, Jie ; Yuan, Zhichao ; Yao, Shan ; Xia, Chunhe ; Wei, Qing
Abstract :
Attack intention recognition is the process of inferring an attacker´s intention from the observed attack behaviors, which is based on some attack scenario. The common methods of modeling attack scenario are attack tree and attack graph, but these methods are not suitable for attack intention recognition. In this paper, we focus on the method of generating attack scenarios. We propose a novel model of attack scenario for attack intention recognition. Then the generating algorithm is given to generate attack scenario. We demonstrate the validity of this method with an experimental network at last.
Keywords :
Computational modeling; Hidden Markov models; Intrusion detection; Libraries; Probes; Servers; attack intention recognition; attack scenario; generating algorithm;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2011 International Conference on
Conference_Location :
Chengdu, China
Print_ISBN :
978-1-4577-1540-2
DOI :
10.1109/ICCIS.2011.156