2011
DOI: 10.1002/sec.337
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A beneficial analysis of deployment knowledge for key distribution in wireless sensor networks

Abstract: Because of the resource constraints on sensor networks, many recent key management schemes exploit the location of nodes in order to establish pairwise keys. Despite these efforts, location discovery for sensor networks is very difficult because existing schemes have failed to consider changes in the signal range and the deployment error. As a result, network performance may accidentally decrease, whereas costs increase. In this paper, we used the theory of the signal range and deployment error knowledge to an… Show more

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Cited by 12 publications
(9 citation statements)
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References 16 publications
(30 reference statements)
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“…In addition, our scheme can also be developed and applied for key distributions in wireless sensor networks [11].…”
Section: Resultsmentioning
confidence: 99%
“…In addition, our scheme can also be developed and applied for key distributions in wireless sensor networks [11].…”
Section: Resultsmentioning
confidence: 99%
“…Zhou et al combined the pre-distributed pairwise key scheme with the hash chain, and presented an efficient and scalable pairwise key predistribution scheme using deployment knowledge in [20]. Considering that location discovery for sensor networks is very difficult, [21] uses the theory of the signal range and deployment error knowledge to analyze sensor nodes location information, and proved that novel deployment knowledge is also expected to provide superior performance with different types of key distribution schemes.…”
Section: Key Establishment Schemes Employing Deployment Knowledge mentioning
confidence: 99%
“…In recent years, issue of key distribution and user authentication mechanisms received a substantial attention from researchers . Various schemes to authenticate users in WSNs have been designed as discussed in the review of , but most of these schemes are at risk of one or other security attacks.…”
Section: Introductionmentioning
confidence: 99%