Feature Engineering for Detection of Wormhole Attacking in Mobile Ad Hoc Networks with Machine Learning Methods

Karlsson, Jonny; Westerlund, Magnus; Dooley, Laurence S. and Pulkkis, Göran (2014). Feature Engineering for Detection of Wormhole Attacking in Mobile Ad Hoc Networks with Machine Learning Methods. In: Seminar on Current Topics in Business,Information Technology and Analytics (BITA’14) (Karlsson, Jonny and Westerlund, Magnus eds.), 13 Oct 2014, Helsinki, Arcada University, Finland, pp. 3–11.

URL: http://dspace.arcada.fi:8080/jspui/bitstream/10478...

Abstract

Due to the self-configuring nature of a Mobile Ad Hoc Network (MANET), each node must participate in the routing process, in addition to its other activities. Therefore, routing in a MANET is especially vulnerable to malicious node activity leading to potentially severe disruption in network communications. The wormhole attack is a particularly severe MANET routing threat since it is easy to launch, can be launched in several modes, difficult to detect, and can cause significant communication disruption. In this paper we establish a practice for feature engineering of network data for wormhole attack prevention and detection with intrusion detection methods based on machine learning.

Viewing alternatives

Download history

Item Actions

Export

About

Recommendations