Cross-Feature Analysis for Detecting Ad-Hoc Routing Anomalies

With the proliferation of wireless devices, mobile ad hoc networking (MANET) has become a very exciting and important technology due to its characteristics of open medium and dynamic topology among others. However, MANETs are more vulnerable than wired networks. Existing security mechanisms developed for wired networks need be redesigned for MANET. In this paper, we discuss the problem of intrusion detection in MANET. The focus of our research is on techniques for automatically constructing anomaly detection models that are capable of detecting new (or unknown) attacks. We introduce a new data mining method that uses “cross-feature analysis” to capture the inter-feature correlation patterns in normal traffic. These patterns can be used as normal profiles to detect deviation (or anomalies) caused by attacks. We have implemented our method with two well known ad-hoc routing protocols, namely, Dynamic Source Routing (DSR) and Ad-hoc On-Demand Distance Vector (AODV), and have conduc...

• Type: Conference
• Year: 2003
• Where: ICDCS
• Authors: Yi-an Huang, Wei Fan, Wenke Lee, Philip S. Yu
• Keywords: Anomaly Detection, Data Mining Method, Distributed And Parallel Computing, ICDCS 2003, Wired Networks