Title :
Improving intrusion detection through merging heterogeneous IP data
Author :
Zhu, Wenjie ; Wang, Qiang
Author_Institution :
Dept. of Autom., Univ. of Sci. & Technol. of China (USTC), Hefei, China
Abstract :
Intrusion Detection is an important and classical research area in network security. It is observed that existing intrusion detection methods usually research all data in the network as a whole. However, in reality, data in the network can be categorized into two types: upward IP data and downward IP data. These two types of IP data may play different roles in intrusion detection process. Based on this observation, a novel intrusion detection method called Duplex Traffic Joint Analyzing(DTJA) method is proposed so as to consider both upward and downward IP data more specifically. With this method, intrusion clues can be found more effectively and efficiently. Experiment results indicate this method is feasible.
Keywords :
IP networks; security of data; telecommunication security; telecommunication traffic; DTJA method; downward IP data; duplex traffic joint analyzing method; heterogeneous IP data; intrusion clues; intrusion detection improvement; intrusion detection process; network security; upward IP data; Data privacy; Dictionaries; IP networks; Intrusion detection; Neural networks; Support vector machines; Vectors; Downward IP Data; Intrusion detection; Upward IP Data;
Conference_Titel :
Information and Automation (ICIA), 2012 International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4673-2238-6
Electronic_ISBN :
978-1-4673-2236-2
DOI :
10.1109/ICInfA.2012.6246794
