Hash Chains Sensornet: A Key Predistribution Scheme for Distributed Sensor Networks Using Nets and Hash Chains

Key management is an essential functionality for a security protocol; particularly for implementations to low cost devices of a distributed sensor networks (DSN)–a prototype of Internet of Things (IoT). Constraints in resources of the constituent devices of a low cost IoT (sensors of DSN) restricts implementations of computationally heavy public key cryptosystems. This led to adaptation of the novel key predistribution technique in symmetric key platform to efficiently tackle the problem of key management for these resource starved networks. Initial proposals use random graphs, later key predistribution schemes (KPS) exploit combinatorial approaches to assure essential design properties. Combinatorial designs like a (v, b, r, k)– configuration which forms a µ–CID are effective schemes to design KPS. A net in a vector space is a set of cosets of certain kind of subspaces called partial spread. A µ(v, b, r, k)–CID can be formed from a net. In this paper, we propose a key predistribution scheme for DSN, named as Sensornet, using a net. We observe that any deterministic KPS suffer from “smart attack” and hence devise a generic method to eliminate it. Resilience of a KPS can be improved by clever Hash Chains technique introduced by Bechkit et al. We improve our Sensornet to achieve Hash Chains Sensornet (HC(Sensornet)) by the applications of these two generic methods. Effectiveness of Sensornet and HC(Sensornet) in term of crucial metrics in comparison to other prominent schemes has been theoretically established

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts