2010 Second International Workshop on Education Technology and Computer Science 2010
DOI: 10.1109/etcs.2010.395
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A Lightweight Key Management Scheme for Wireless Sensor Networks

Abstract: Key management is the core of security protocol for wireless sensor networks deployed in the hostile environment. Due to the strict resource constraints, traditional asymmetric key cryptosystems, such as public/private key based schemes, are infeasible for the wireless sensor networks. The existing random key based key pre-distribution schemes only provide some level of network resilience, as the number of compromised nodes increasing, the fraction of affected pairwise keys will increase quickly. As a result, … Show more

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Cited by 6 publications
(2 citation statements)
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“…In WSN, the lightweight scheme for key management [ 16 ] is employed to reduce the resource consumption and acts as the building block for all security mechanisms. This scheme relies on numerical sequences in order to allow each deployed sensor node for estimating distinct pairwise keys with its neighbors.…”
Section: Various Authentication Protocols In Wireless Sensor Netwomentioning
confidence: 99%
“…In WSN, the lightweight scheme for key management [ 16 ] is employed to reduce the resource consumption and acts as the building block for all security mechanisms. This scheme relies on numerical sequences in order to allow each deployed sensor node for estimating distinct pairwise keys with its neighbors.…”
Section: Various Authentication Protocols In Wireless Sensor Netwomentioning
confidence: 99%
“…It has been used to handle the concept of partial truth using linguistic variables that may range between completely true and completely false. Fuzzy set contains elements that belong to a graded membership function within interval [0, 1], not crisp set where each element belongs to specific set [19] [20]. A fuzzy logic controller consists of sequence of steps, starting with fuzzifier step that takes the crisp input from the system and determines the degree that it belongs to the appropriate fuzzy sets.…”
Section: Fuzzy Logicmentioning
confidence: 99%