scholarly journals A Portable Random Key Predistribution Scheme for Distributed Sensor Network

2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
Shihui Zheng ◽  
Yuan Tian ◽  
Lei Jin ◽  
Yu Yang

A distributed sensor network (DSN) can be deployed to collect information for military or civilian applications. However, due to the characteristics of DSNs such as limited power, key distribution for a distributed sensor network is complex. In this paper, a neighbor-based path key establishing method and a seed-based algorithm are put forward to improve the original random key pre-distribution scheme. The new scheme is portable because it is independent of the routing protocol. Moreover, the connectivity of the entire network also approaches 1. In particular, the new scheme can keep high connectivity by setting a small amount of redundancy in parameter values when the number of neighbors drops because of the node dormancy or death. The resilience against node capture in our scheme is not lower than that in thel-path scheme and the basic schemes when the number of hops in a path is larger than 5, and the simulation result shows that the efficiency of our scheme is also slightly higher.

2012 ◽  
Vol 263-266 ◽  
pp. 920-925 ◽  
Author(s):  
Alan Dahgwo Yein ◽  
Cheng Yeh Chen ◽  
Te Cheng Hsu ◽  
Wen Shyong Hsieh ◽  
Jiun An Lin

Wireless sensor networks have been widely used in many areas, such as earthquake monitoring, building structure monitoring, and military surveillance. In this work, we focus on the wireless sensor network deployed in the battlefield, using random key predistribution scheme. Based on the node cloning attack, we proposed a new attack scheme, called compromised key redistribution attack, and discussed related attack scenarios. Furthermore, we have exposed that, when the overlapping factor of compromised key set is larger than 0.05, it is almost 90% that the number of distinct compromised keys is 10.5% of the original key pool. This result helps the adversary estimate the approximated size of original key pool by calculating the overlapping factor, thus calculate the probability that malicious nodes successfully establish malicious connections with legitimate nodes.


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