Abstract-With the development of wireless communication technologies which considerably contributed to the development of wireless sensor networks (WSN), we have witnessed an everincreasing WSN based applications which induced a host of research activities in both academia and industry. Since most of the target WSN applications are very sensitive, security issue is one of the major challenges in the deployment of WSN. One of the important building blocks in securing WSN is key management. Traditional key management solutions developed for other networks are not suitable for WSN since WSN networks are resource (e.g. memory, computation, energy) limited. Key pre-distribution algorithms have recently evolved as efficient alternatives of key management in these networks. In the key predistribution systems, secure communication is achieved between a pair of nodes either by the existence of a key allowing for direct communication or by a chain of keys forming a key-path between the pair. In this paper, we propose methods which bring prior knowledge of network characteristics and application constraints into the design of key pre-distribution schemes, in order to provide better security and connectivity while requiring less resources. Our methods are based on casting the prior information as a graph. Motivated by this idea, we also propose a class of quasisymmetric designs referred here to as g-designs. These produce key pre-distribution schemes that significantly improve upon the existing constructions based on unital designs. We give some examples, and point out open problems for future research. Index Terms-Balanced incomplete block design, quasisymmetric design, key pre-distribution, sensor networks, graphs.
Ding et al. REF considered prior knowledge of network characteristics and application constraints in terms of communication needs between sensor nodes and proposed methods to design key pre-distribution schemes in order to provide better security and connectivity.
Key Pre-Distributions From Graph-Based Block Designs
ArXiv
ArXiv
Computer Science