Wireless sensor network internal attacker identification with multiple evidence by dempster-shafer theory

Authors:
Muhammad Ahmed;Xu Huang;Dharmendra Sharma;Li Shutao
Affiliations:
Faculty of Information Sciences and Engineering, University of Canberra, Australia;Faculty of Information Sciences and Engineering, University of Canberra, Australia;Faculty of Information Sciences and Engineering, University of Canberra, Australia;College of Electrical and Information Engineering, Huana University, Changsha, P.R. China
Venue:
ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part II
Year:
2012

Citing 4
Cited 0

Mitigating routing misbehavior in mobile ad hoc networks

MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Efficient tracing of failed nodes in sensor networks

WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Combination of multiple diverse classifiers using belief functions for handling data with imperfect labels

Expert Systems with Applications: An International Journal
Timing control for protecting from internal attacks in wireless sensor networks

ICOIN '12 Proceedings of the The International Conference on Information Network 2012

Quantified Score

Hi-index	0.00

Visualization

Abstract

Wireless sensor Network (WSN) is known to be vulnerable to variety of attacks due to the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or insider attacker has gained prominence and poses the most challenging attacks to WSN. Many works has been done to secure WSN from internal attacker but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure WSN need to find the internal attacker. Normally, internal attacker node behavioral pattern is different from the other neighbor good nodes in the system, but neighbor node can be attacked as well. In this paper, we use Dempster-Shafer theory (DST) of combined multiple evidence to identify the malicious or internal attacker in WSN. This theory reflects with the uncertain event or uncertainty as well as uncertainty of the observation. Moreover, it gives a numerical procedure for fusing together multiple pieces of evidence from unreliable neighbor with higher degree of conflict reliability.