On the Security of Wireless Sensor Networks via Compressive Sensing

Abstract

Due to energy limitation of sensor nodes, the conventional security algorithms with high computation complexity are not suitable for wireless sensor networks (WSNs). We propose a compressive sensing-based encryption for WSNs, which provides both signal compression and encryption guarantees, without introducing additional computational cost of a separate encryption protocol. In this paper, we also discuss the information-theoretical and computational secrecy of compressive sensing algorithm. For proposed WSN, if only a fraction of randomizer bits is stored by an eavesdropper, then the probability that he/she cannot obtain any information about the plaintext approaches zero. Simulation results show a trade-off can be made between the sparsity of a random measurement matrix and the number of sensor nodes used to reconstruct the original signal at the fusion center.Keywords Wireless sensor networks • Compressive sensing • Perfect secrecy and data reconstruction IntroductionSensor nodes in wireless sensor networks (WSNs) are inherently resourceconstrained. These battery-operated nodes have limited processing capability and low storage capacity. In most practical situations, sensor nodes are unattended and even deployed in the hostile environments, which demands careful security consideration in the design of WSNs. Because of those constraints, the conventional security mechanisms with high computation complexity are not suitable for WSNs.

Speeding Up Exact Algorithms for Maximizing Lifetime of WSNs Using Multiple Cores

“…The basic idea is to decompose the graph into biconnected subgraphs and formulate the problem on each subgraph as an integer linear programming problem, which is solved by an integer linear programming solver. Besides routing, energy efficiency is also considered in other contexts such as compressive sensing-based encryption [9] and rechargeable sensor networks [10].…”

“…reverse the directions of edges in and perform a breadth-first search from the sink (8) if all vertices are visited then (9) construct subproblem with as the network; (10) include to ; (11) return ; Algorithm 4: decomp fixing parent.…”