Predistribution For Wireless Sensor Networks Research Articles

Nested block design as key pre-distribution in wireless sensor networks

An accumulation of wireless sensor nodes is combined together to form the Wireless Sensor Networks. The sensor nodes are distributed haphazardly without any decided method into a natural setting, which is generally inhospitable and it is difficult to provide key-chains to each node for security as they are haphazardly distributed. In this paper, we use Nested Block Design (NBD) as Key Pre-distribution Scheme (KPS) and found out that NBD support large networks with fewer keys in each node than Symmetric Balanced Incomplete Block Designs (SBIBD) and Transversal Design (TD[Formula: see text]), provide higher resiliency than SBIBDs and better connectivity than TD[Formula: see text], tradeoff between local connectivity and resiliency ([Formula: see text]) is lower than SBIBD but more than TD[Formula: see text] and key-node ratio ([Formula: see text]) is same for [Formula: see text] but lower than SBIBD.

New key pre‐distribution scheme based on combinatorial design for wireless sensor networks

Key pre-distribution in wireless sensor networks is an important area of research due to limited resource availability in sensor nodes. In this study, the authors propose a novel key pre-distribution scheme for wireless sensor networks based on combinatorial design. The proposed scheme is used to assign secret keys to the sensor nodes so that they can securely communicate among themselves. It also aims to decrease the key storage overhead and improve the overall resiliency of the network. They use the ratio of links broken/affected and the ratio of nodes disconnected to measure the resiliency when some sensor nodes are compromised in the network. They observed that the proposed scheme reduces the key storage overhead in the network while maintaining the desired connectivity among all the sensor nodes. Further, the proposed scheme is more resilient than the majority of existing schemes present in the literature.

On Connectivity and Robustness in Random Intersection Graphs

Random intersection graphs have received much attention recently and been used in a wide range of applications ranging from key predistribution in wireless sensor networks to modeling social networks. For these graphs, each node is equipped with a set of objects in a random manner, and two nodes have an undirected edge in between if they have at least one object in common. In this paper, we investigate connectivity and robustness in a general random intersection graph model. Specifically, we establish sharp asymptotic zero-one laws for k-connectivity and k-robustness, as well as the asymptotically exact probability of k-connectivity, for any positive integer k. The k-connectivity property quantifies how resilient is the connectivity of a graph against node or edge failures, while k-robustness measures the effectiveness of local-information-based consensus algorithms (that do not use global graph topology information) in the presence of adversarial nodes. In addition to presenting the results under the general random intersection graph model, we consider two special cases of the general model, a binomial random intersection graph and a uniform random intersection graph, which both have numerous applications as well. For these two specialized graphs, our results on asymptotically exact probabilities of k-connectivity and asymptotic zero-one laws for k-robustness are also novel in the literature.

Secure Strategy for Key Pre-Distribution in Wireless Sensor Networks

Wireless sensor networks (WSN) are a collection of sensor nodes, which is deployed spatially among various environments. WSNs are deployed in environments where wired networks are difficult to set up. They are mainly used to record sensitive information regarding physical or environmental conditions. As they collect sensitive information, secure and accurate transmission of data is important. For secure transmission of data, key management is a corner stone in wireless sensor networks. Wireless sensor networks are infrastructure less. Due to this reason, key distribution among increasing number of nodes by third parties is a challenging problem. Hence, symmetric key pre-distribution algorithms are introduced for key distribution. However, most schemes suffer from low scalability, high storage overhead and it is difficult to implement security with existing solutions. In order to provide good key sharing and secure connectivity, an asymmetric algorithm called elliptical curve cryptography (ECC) will be used. After collecting data from deployed environment, sensor nodes will send data to sink node, which receives data and process the information. Data will be routed to sink node in secure environment using shortest path routers. The schemes will be implemented in java programming language and results would be derived to show/compared for more efficiency in terms of secure connectivity, storage overhead, computational cost and communication cost.

Secure Key Pre-distribution in Wireless Sensor Networks Using Combinatorial Design and Traversal Design Based Key Distribution

Security is an indispensable concern in Wireless Sensor Network (WSN) due to the presence of potential adversaries. For secure communication in infrastructureless sensor nodes various key predistribution have been proposed. In this paper we have evaluated various existing deterministic, probabilistic and hybrid type of key pre-distribution and dynamic key generation algorithms for distributing pair-wise, group-wise and network-wise keys and we have propose a key predistribution scheme using deterministic approach based on combinatorial design and traversal design which will improve the resiliency and achieve sufficient level of security in the network.This design can be used where large number of nodes are to be deployed in the WSN.

A new key predistribution scheme for general and grid-group deployment of wireless sensor networks

Key predistribution for wireless sensor networks has been a challenging field of research because stringent resource constraints make the key predistribution schemes difficult to implement. Despite this, key predistribution scheme is regarded as the best option for key management in wireless sensor networks. Here, the authors have proposed a new key predistribution scheme. This scheme exhibits better performance than existing schemes of its kind. Moreover, our scheme ensures constant time of key establishment between two nodes. We provide some bounds on the resiliency of this scheme. Next, we use this new key predistribution scheme in a grid-group deployment of sensor nodes. The entire deployment zone is broken into square regions. The sensor nodes falling within a single square region can communicate directly. Sensor nodes belonging to different square regions can communicate by means of special nodes deployed in each of the square region. We measure the resiliency in terms of fraction of links disconnected as well as fraction of nodes and regions disconnected. We show that our key predistribution scheme when applied to grid-group deployment performs better than standard models in existence.

Secure Key Pre-distribution in Wireless Sensor Networks Using Combinatorial Design and Traversal Design Based Key Distribution

Security is an indispensable concern in Wireless Sensor Network (WSN) due to the presence of potential adversaries. For secure communication in infrastructure less sensor nodes various key pre distribution have been proposed. In this paper we have evaluated various existing deterministic, probabilistic and hybrid type of key pre distribution and dynamic key generation algorithms for distributing pair-wise, group-wise and network-wise keys and we have propose a key pre distribution scheme using deterministic approach based on combinatorial design and traversal design which will improve the resiliency and achieve sufficient level of security in the network. This design can be used where large number of nodes are to be deployed in the WSN.

A Novel Key Pre-distribution for Wireless Sensor Networks

Abstract To establish the two key in wireless sensor network is a basic security services, forming the basis other security services, such as authentication and encrypted. However, due to the sensor network resource constraints on to establish the two key not wireless sensor networks trivial tasks. The existing key, pre-alpha-ever scheme compromise node number and a minor part however influence key will increase quickly. As a result, a small compromise the number of node may affect the most adversaries. This paper proposes an improved key management wireless sensor network plan, take advantage of one-way hash function to alleviate the influence of compromise the sensor high sensor nodes. At the same time, this method does not affect the connection between neighboring sensor node. The analysis shows that compared with the existing plan which has good network resilience against node capture attack.

Distinct Difference Configurations: Multihop Paths and Key Predistribution in Sensor Networks

A distinct difference configuration is a set of points in <emphasis emphasistype="italic" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><formula formulatype="inline"><tex Notation="TeX">$\BBZ ^{2}$</tex></formula></emphasis> with the property that the vectors ( <emphasis emphasistype="boldital" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">difference vectors</emphasis> ) 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 <emphasis emphasistype="italic" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><formula formulatype="inline"> <tex Notation="TeX">$k$</tex></formula></emphasis> -hop coverage of a distinct difference configuration to be the number of distinct vectors that can be expressed as the sum of <emphasis emphasistype="italic" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><formula formulatype="inline"> <tex Notation="TeX">$k$</tex></formula></emphasis> 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 <emphasis emphasistype="italic" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><formula formulatype="inline"> <tex Notation="TeX">$k$</tex></formula></emphasis> -hop coverage of a distinct difference configuration with <emphasis emphasistype="italic" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><formula formulatype="inline"> <tex Notation="TeX">$m$</tex></formula></emphasis> points, and exploit a connection with <emphasis emphasistype="italic" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><formula formulatype="inline"><tex Notation="TeX">$B_{h}$</tex> </formula></emphasis> sequences to construct configurations with maximal <emphasis emphasistype="italic" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><formula formulatype="inline"><tex Notation="TeX">$k$</tex> </formula></emphasis> -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.

Location-based pairwise key predistribution for wireless sensor networks

A practical pairwise key distribution scheme is necessary for wireless sensor networks since sensor nodes are susceptible to physical capture and constrained in their resources. In this paper, we investigate a simple and practical scheme that achieves higher connectivities and perfect resilience with less resources, even in case of deployment errors.

Random key predistribution for wireless sensor networks using deployment knowledge

We consider a key distribution scheme for wireless sensor networks which uses deployment knowledge. Deployment is modeled as a grid of hexagonal clusters, into centers of which the sensor nodes are dropped according to a given probability distribution (e.g. a Gaussian one). We consider sensor connectivity in a random intersection graph model, instead of the more commonly used in literature G(n, p) graph model. While the latter is easier to analyze, the former is much more suitable to modeling sensor network key distribution. We provide analytical, asymptotic results showing how to pick parameters (key pool size |S|, the number of chosen keys d) depending on the number of deployed nodes in order to assure global connectivity of the network, and estimate the diameter of the network for the given parameters.

Grid-Based Key Pre-Distribution in Wireless Sensor Networks

In this paper, we introduce a grid-based key pre-distribution scheme in wireless sensor networks, which aims to improve the connectivity and resiliency while maintaining a reasonable overhead. We consider simplification of the key establishment logic and enhancement of the connectivity via plat polynomial assignment on a three-dimensional grid for node allocation and keying material assignment. We demonstrate that our scheme results in improvements via a detailed discussion on the connectivity, resource usage, security features and resiliency. A comparison with other relevant works from the literature along with a demonstrated implementation on typical sensor nodes shows the feasibility of the introduced scheme and its applicability for large networks.

Two-level Key Pool Design-based Random Key Pre-distribution in Wireless Sensor Networks

In this paper, the random key pre-distribution scheme introduced in ACM CCS'02 by Eschenauer and Gligor is reexamined, and a generalized form of key establishment is introduced. As the communication overhead is one of the most critical constraints of any successful protocol design, we introduce an alternative scheme in which the connectivity is maintained at the same level as in the original work, while the communication overhead is reduced by about 40% of the original overhead, for various carefully chosen parameters. The main modification relies on the use of a two-level key pool design and two round assignment/key establishment phases. Further analysis demonstrates the efficiency of our modification.

Tree-based key predistribution for wireless sensor networks

The establishment of secure links between neighboring nodes is one of the most challenging problems in wireless sensor networks. In this article, we present an efficient key predistribution scheme for sensor networks such that pairwise keys are defined by iterated hash computations based on a tree structure. Our scheme can be regarded as an improvement of HARPS, Ramkumar and Memon (IEEE J Sel Area Commun 23(3):611---621, 2005),or a generalization of Leighton and Micali's scheme (Lect Notes Comput Sci 773:456---479, 1994). We rigorously analyze our scheme focusing on the resiliency of the network and hash computational complexity for each node and compare the performance with existing schemes. Specifically, we show that our scheme provides stronger resiliency and requires less hash computational complexity than HARPS.

Group-based key predistribution for wireless sensor networks

Many key predistribution techniques have been developed recently to establish pairwise keys between sensor nodes in wireless sensor networks. To further improve these schemes, researchers have also proposed to take advantage of the sensors' expected locations and discovered locations to help the predistribution of the keying materials. However, in many cases, it is very difficult to deploy sensor nodes at their expected locations or guarantee the correct location discovery at sensor nodes in hostile environments. In this article, a group-based deployment model is developed to improve key predistribution. In this model, sensor nodes are only required to be deployed in groups. The critical observation in the article is that the sensor nodes in the same group are usually close to each other after deployment . This deployment model is practical; it greatly simplifies the deployment of sensor nodes, while still providing an opportunity to improve key predistribution. Specifically, the article presents a novel framework for improving key predistribution using the group-based deployment knowledge. This framework does not require the knowledge of the sensors' expected or discovered locations and is thus suitable for applications where it is difficult to deploy the sensor nodes at their expected locations or correctly estimate the sensors' locations after deployment. To seek practical key predistribution schemes, the article presents two efficient instantiations of this framework, a hash key-based scheme and a polynomial-based scheme . The evaluation shows that these two schemes are efficient and effective for pairwise key establishment in sensor networks; they can achieve much better performance than the previous key predistribution schemes when the sensor nodes are deployed in groups.

A canonical seed assignment model for key predistribution in wireless sensor networks

A promising solution for trust establishment in wireless sensor networks is the assignment of cryptographic seeds (keys, secrets, etc.) to sensor nodes prior to network deployment, known as key predistribution . In this article, we propose a canonical seed assignment model for key predistribution characterizing seed assignment in terms of the probability distribution describing the number of nodes receiving each seed and the algorithm for seed assignment. In addition, we present a sampling framework for seed assignment algorithms in the canonical model. We propose a probabilistic k -connectivity model for randomly deployed secure networks using spatial statistics and geometric random graph theory. We analyze key predistribution schemes in the canonical model in terms of network connectivity and resilience to node capture. The analytical results can be used to determine the average or worst-case connectivity or resilience to node capture for a key predistribution scheme. Furthermore, we demonstrate the design of new key predistribution schemes and the inclusion of existing schemes in the canonical model. Finally, we present a general approach to analyze the addition of nodes to an existing secure network and derive results for a well-known scheme.