Mitigating routing misbehavior in mobile ad hoc networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
SIA: secure information aggregation in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Modeling Node Compromise Spread in Wireless Sensor Networks Using Epidemic Theory
WOWMOM '06 Proceedings of the 2006 International Symposium on on World of Wireless, Mobile and Multimedia Networks
A probabilistic voting-based filtering scheme in wireless sensor networks
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Fuzzy adaptive threshold determining in the key inheritance based sensor networks
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Key inheritance-based false data filtering scheme in wireless sensor networks
ICDCIT'06 Proceedings of the Third international conference on Distributed Computing and Internet Technology
Statistical en-route filtering of injected false data in sensor networks
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.00 |
Wireless sensor networks are vulnerable to false data injection attacks. In these, adversaries inject false reports into the network using compromised nodes, with the goal of deceiving the base station and depleting the energy resources of forwarding nodes. Several filtering schemes, and the adaptive versions of them, have been proposed to detect and drop such false reports during the forwarding process. In this paper, we propose a fuzzy-based framework to achieve adaptive filtering of false reports. A fuzzy rule-based system controls the security level of the filtering scheme through the determination of the required number of endorsements in every report. Compared to existing adaptive solutions, the proposed method uses more practical factors for the determination and can be applied to the network, regardless of scale. The proposed method can provide energy saving and sufficient resilience against false data injection attacks.