Hierarchical Grid-Based Pairwise Key Pre-distribution in Wireless Sensor Networks

The security of wireless sensor networks is an active topic of research where both symmetric and asymmetric key cryptography issues have been studied. Due to their computational feasibility on typical sensor nodes, symmetric key algorithms that use the same key to encrypt and decrypt messages have been intensively studied and perfectly deployed in such environment. Because of the wireless sensor's limited infrastructure, the bottleneck challenge for deploying these algorithms is the key distribution. For the same reason of resources restriction, key distribution mechanisms which are used in traditional wireless networks are not efficient for sensor networks. To overcome the key distribution problem, several key pre-distribution algorithms and techniques that assign keys or keying material for the networks nodes in an offline phase have been introduced recently. In this paper, we introduce a supplemental distribution technique based on the communication pattern and deployment knowledge modeling. Our technique is based on the hierarchical grid deployment. For granting a proportional security level with number of dependent sensors, we use different polynomials in different orders with different weights. In seek of our proposed work's value, we provide a detailed analysis on the used resources, resulting security, resiliency, and connectivity compared with other related works.Comment: 13 pages, 9 figures, 2 tables, to appear in the International Journal of Networks and Securit

Dynamic key ring update mechanism for mobile wireless sensor networks

Key distribution is an important issue to provide security in Wireless Sensor Networks (WSNs). Many of the key pre-distribution schemes proposed for static WSNs perform poorly when they are applied to Mobile Wireless Sensor Networks (MWSNs). In this paper, we propose Dynamic Key Ring Update (DKRU) mechanism for MWSNs. The aim of DKRU mechanism is to enable sensor nodes to update their key rings periodically during movement, by observing the frequent keys in their neighbors. Our mechanism can be used together with different key pre-distribution schemes and it helps to increase the performance of them. For the performance evaluation basis, we used our mechanism together with a location based key pre-distribution scheme. Our results show that DKRU mechanism increases the local and global connectivity when it is applied to MWSNs. Moreover, our mechanism does not cause a significant degradation in network resiliency

Distinct difference configurations: multihop paths and key predistribution in sensor networks

A distinct difference configuration is a set of points in Z2 with the property that the vectors (difference vectors) connecting any two of the points are all distinct. Many specific examples of these configurations have been previously studied: the class of distinct difference configurations includes both Costas arrays and sonar sequences, for example. Motivated by an application of these structures in key predistribution for wireless sensor networks, we define the k-hop coverage of a distinct difference configuration to be the number of distinct vectors that can be expressed as the sum of k or fewer difference vectors. This is an important parameter when distinct difference configurations are used in the wireless sensor application, as this parameter describes the density of nodes that can be reached by a short secure path in the network. We provide upper and lower bounds for the k-hop coverage of a distinct difference configuration with m points, and exploit a connection with Bh sequences to construct configurations with maximal k-hop coverage. We also construct distinct difference configurations that enable all small vectors to be expressed as the sum of two of the difference vectors of the configuration, an important task for local secure connectivity in the application

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

A unified approach to combinatorial key predistribution schemes for sensor networks

There have been numerous recent proposals for key predistribution schemes for wireless sensor networks based on various types of combinatorial structures such as designs and codes. Many of these schemes have very similar properties and are analysed in a similar manner. We seek to provide a unified framework to study these kinds of schemes. To do so, we define a new, general class of designs, termed “partially balanced t-designs”, that is sufficiently general that it encompasses almost all of the designs that have been proposed for combinatorial key predistribution schemes. However, this new class of designs still has sufficient structure that we are able to derive general formulas for the metrics of the resulting key predistribution schemes. These metrics can be evaluated for a particular scheme simply by substituting appropriate parameters of the underlying combinatorial structure into our general formulas. We also compare various classes of schemes based on different designs, and point out that some existing proposed schemes are in fact identical, even though their descriptions may seem different. We believe that our general framework should facilitate the analysis of proposals for combinatorial key predistribution schemes and their comparison with existing schemes, and also allow researchers to easily evaluate which scheme or schemes present the best combination of performance metrics for a given application scenario