Title :
Grouping-Enhanced Resilient Probabilistic En-Route Filtering of Injected False Data in WSNs
Author :
Li, Jianzhong ; Yu, Lei ; Gao, Hong ; Xiong, Shuguang
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China
fDate :
5/1/2012 12:00:00 AM
Abstract :
In wireless sensor networks, the adversary may inject false reports to exhaust network energy or trigger false alarms with compromised sensor nodes. In response to the problems of existing schemes on the security resiliency, applicability and filtering effectiveness, this paper proposes a scheme, referred to as Grouping-enhanced Resilient Probabilistic En-route Filtering (GRPEF). In GRPEF, an efficient distributed algorithm is proposed to group nodes without incurring extra groups, and a multiaxis division based approach for deriving location-aware keys is used to overcome the threshold problem and remove the dependence on the sink immobility and routing protocols. Compared to the existing schemes, GRPEF significantly improves the effectiveness of the en-route filtering and can be applied to the sensor networks with mobile sinks while reserving the resiliency.
Keywords :
distributed algorithms; routing protocols; telecommunication security; wireless sensor networks; efficient distributed algorithm; grouping-enhanced resilient probabilistic en-route filtering; injected false data; location-aware keys; mobile sinks; multiaxis division based approach; routing protocols; security resiliency; sink immobility; wireless sensor networks; Authentication; Mobile communication; Probabilistic logic; Routing; Sensors; Shape; Wireless sensor networks; Wireless sensor networks; en-route filtering; false data injection; mobile sink.; network security; node compromise;
Journal_Title :
Parallel and Distributed Systems, IEEE Transactions on
DOI :
10.1109/TPDS.2011.217