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

A Generalised Formula for Calculating the Resilience of Random Key Predistribution Schemes

A commonly used metric for comparing the resilience of key predistribution schemes is \fail_s, which measures the proportion of network connections which are `broken\u27 by an adversary which has compromised $s$ nodes. In `Random key predistribution schemes for sensor networks\u27, Chan, Perrig and Song present a formula for measuring the resilience in a class of random key predistribution schemes called $q$-composite schemes. We present a correction to this formula for schemes where more than one key may be used to secure a link between a pair of nodes. Our corrected formula features an additional parameter which makes it applicable to a wider variety of random key predistribution schemes, including the original Eschenauer Gligor scheme. We also present a simplification of the formula for calculating connectivity. We refer to the recent paper by Yum and Lee which also claims to correct the original formula for the $q$-composite scheme. However the resulting formula is complicated, computationally demanding, and hard to understand. The formula which we propose and prove is easily computable and can be applied to a wider range of schemes

On the Role of Expander Graphs in Key Predistribution Schemes for Wireless Sensor Networks

Providing security for a wireless sensor network composed of small sensor nodes with limited battery power and memory can be a non-trivial task. A variety of key predistribution schemes have been proposed which allocate symmetric keys to the sensor nodes before deployment. In this paper we examine the role of expander graphs in key predistribution schemes for wireless sensor networks. Roughly speaking, a graph has good expansion if every `small\u27 subset of vertices has a `large\u27 neighbourhood, and intuitively, expansion is a desirable property for graphs of networks. It has been claimed that good expansion in the product graph is necessary for `optimal\u27 networks. We demonstrate flaws in this claim, argue instead that good expansion is desirable in the intersection graph, and discuss how this can be achieved. We then consider key predistribution schemes based on expander graph constructions and compare them to other schemes in the literature. Finally, we propose the use of expansion and other graph-theoretical techniques as metrics for assessing key predistribution schemes and their resulting wireless sensor networks

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

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.

Secure Protocols for Key Pre-distribution, Network Discovery, and Aggregation in Wireless Sensor Networks

The term sensor network is used to refer to a broad class of networks where several small devices, called sensors, are deployed in order to gather data and report back to one or more base stations. Traditionally, sensors are assumed to be small, low-cost, battery-powered, wireless, computationally constrained, and memory constrained devices equipped with some sort of specialized sensing equipment. In many settings, these sensors must be resilient to individual node failure and malicious attacks by an adversary, despite their constrained nature. This thesis is concerned with security during all phases of a sensor network's lifetime: pre-deployment, deployment, operation, and maintenance. This is accomplished by pre-loading nodes with symmetric keys according to a new family of combinatorial key pre-distribution schemes to facilitate secure communication between nodes using minimal storage overhead, and without requiring expensive public-key operations. This key pre-distribution technique is then utilized to construct a secure network discovery protocol, which allows a node to correctly learn the local network topology, even in the presence of active malicious nodes. Finally, a family of secure aggregation protocols are presented that allow for data to be efficiently collected from the entire network at a much lower cost than collecting readings individually, even if an active adversary is present. The key pre-distribution schemes are built from a family of combinatorial designs that allow for a concise mathematical analysis of their performance, but unlike previous approaches, do not suffer from strict constraints on the network size or number of keys per node. The network discovery protocol is focused on providing nodes with an accurate view of the complete topology so that multiple node-disjoint paths can be established to a destination, even if an adversary is present at the time of deployment. This property allows for the use of many existing multi-path protocols that rely on the existence of such node-disjoint paths. The aggregation protocols are the first designed for simple linear networks, but generalize naturally to other classes of networks. Proofs of security are provided for all protocols