Yunghsiang S. Han

A pairwise key pre-distribution scheme for wireless sensor networks

To achieve security in wireless sensor networks, it is important to be able to encrypt and authenticate messages sent among sensor nodes. Keys for encryption and authentication purposes must be agreed upon by communicating nodes. Due to resource constraints, achieving such key agreement in wireless sensor networks is non-trivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and public-key based schemes, are not suitable for wireless sensor networks. Pre-distribution of secret keys for all pairs of nodes is not viable due to the large amount of memory used when the network size is large. To solve the key pre-distribution problem, two elegant key pre-distribution approaches have been proposed recently [11, 7].In this paper, we propose a new key pre-distribution scheme, which substantially improves the resilience of the network compared to the existing schemes. Our scheme exhibits a nice threshold property: when the number of compromised nodes is less than the threshold, the probability that any nodes other than these compromised nodes is affected is close to zero. This desirable property lowers the initial payoff of smaller scale network breaches to an adversary, and makes it necessary for the adversary to attack a significant proportion of the network. We also present an in depth analysis of our scheme in terms of network resilience and associated overhead.

A pairwise key predistribution scheme for wireless sensor networks

To achieve security in wireless sensor networks, it is important to be able to encrypt and authenticate messages sent between sensor nodes. Before doing so, keys for performing encryption and authentication must be agreed upon by the communicating parties. Due to resource constraints, however, achieving key agreement in wireless sensor networks is nontrivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and other public-key based schemes, are not suitable for wireless sensor networks due to the limited computational abilities of the sensor nodes. Predistribution of secret keys for all pairs of nodes is not viable due to the large amount of memory this requires when the network size is large.In this paper, we provide a framework in which to study the security of key predistribution schemes, propose a new key predistribution scheme which substantially improves the resilience of the network compared to previous schemes, and give an in-depth analysis of our scheme in terms of network resilience and associated overhead. Our scheme exhibits a nice threshold property: when the number of compromised nodes is less than the threshold, the probability that communications between any additional nodes are compromised is close to zero. This desirable property lowers the initial payoff of smaller-scale network breaches to an adversary, and makes it necessary for the adversary to attack a large fraction of the network before it can achieve any significant gain.

A key management scheme for wireless sensor networks using deployment knowledge

To achieve security in wireless sensor networks, it is important to he able to encrypt messages sent among sensor nodes. Keys for encryption purposes must he agreed upon by communicating nodes. Due to resource constraints, achieving such key agreement in wireless sensor networks is nontrivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and public-key based schemes, are not suitable for wireless sensor networks. Pre-distribution of secret keys for all pairs of nodes is not viable due to the large amount of memory used when the network size is large. Recently, a random key pre-distribution scheme and its improvements have been proposed. A common assumption made by these random key pre-distribution schemes is that no deployment knowledge is available. Noticing that in many practical scenarios, certain deployment knowledge may be available a priori, we propose a novel random key pre-distribution scheme that exploits deployment knowledge and avoids unnecessary key assignments. We show that the performance (including connectivity, memory usage, and network resilience against node capture) of sensor networks can he substantially improved with the use of our proposed scheme. The scheme and its detailed performance evaluation are presented in this paper.

A key predistribution scheme for sensor networks using deployment knowledge

To achieve security in wireless sensor networks, it is important to be able to encrypt messages sent among sensor nodes. Keys for encryption purposes must be agreed upon by communicating nodes. Due to resource constraints, achieving such key agreement in wireless sensor networks is nontrivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and public-key-based schemes, are not suitable for wireless sensor networks. Predistribution of secret keys for all pairs of nodes is not viable due to the large amount of memory used when the network size is large. Recently, a random key predistribution scheme and its improvements have been proposed. A common assumption made by these random key predistribution schemes is that no deployment knowledge is available. Noticing that, in many practical scenarios, certain deployment knowledge may be available a priori, we propose a novel random key predistribution scheme that exploits deployment knowledge and avoids unnecessary key assignments. We show that the performance (including connectivity, memory usage, and network resilience against node capture) of sensor networks can be substantially improved with the use of our proposed scheme. The scheme and its detailed performance evaluation are presented in this paper.

A witness-based approach for data fusion assurance in wireless sensor networks

In wireless sensor networks, sensor nodes are spread randomly over the coverage area to collect information of interest. Data fusion is used to process these collected information before they are sent to the base station, the observer of the sensor network. We study the security of the data fusion process in this work. In particular, we propose a witness-based solution to assure the validation of the data sent from data fusion nodes to the base station. We also present the theoretical analysis for the overhead associated with the mechanism, which indicates that even in an extremely harsh environment the overhead is low for the proposed mechanism.

Efficient priority-first search maximum-likelihood soft-decision decoding of linear block codes

The authors present a novel and efficient maximum-likelihood soft-decision decoding algorithm for linear block codes. The approach used here converts the decoding problem into a search problem through a graph that is a trellis for an equivalent code of the transmitted code. A generalized Dijkstras algorithm, which uses a priority-first search strategy, is employed to search through this graph. This search is guided by an evaluation function f defined to take advantage of the information provided by the received vector and the inherent properties of the transmitted code. This function f is used to reduce drastically the search space and to make the decoding efforts of this decoding algorithm adaptable to the noise level. For example, for most real channels of the 35 000 samples tried, simulation results for the (128,64) binary extended BCH code show that the proposed decoding algorithm is fifteen orders of magnitude more efficient in time and in space than that proposed by Wolf (1978). Simulation results for the (104, 52) binary extended quadratic residue code are also given. >

Balanced-energy sleep scheduling scheme for high-density cluster-based sensor networks

In order to conserve battery power in very dense sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. However, determining which of the sensor nodes should be put into the sleep state is non-trivial. As the goal of allowing nodes to sleep is to extend network lifetime, we propose and analyze a Balanced-energy Scheduling (BS) scheme in the context of cluster-based sensor networks. The BS scheme aims to evenly distribute the energy load of the sensing and communication tasks among all the nodes in the cluster, thereby extending the time until the cluster can no longer provide adequate sensing coverage. Two related sleep scheduling schemes, the Distance-based Scheduling (DS) scheme and the Randomized Scheduling (RS) scheme are also studied in terms of the coefficient of variation of their energy consumption. Analytical and simulation results are presented to evaluate the proposed BS scheme. It is shown that the BS scheme extends the clusters overall network lifetime significantly while maintaining a similar sensing coverage compared with the DS and the RS schemes for sensor clusters.

Distributed fault-tolerant classification in wireless sensor networks

Fault-tolerance and data fusion have been considered as two fundamental functions in wireless sensor networks. In this paper, we propose a novel approach for distributed multiclass classification using a fault-tolerant fusion rule for wireless sensor networks. Binary decisions from local sensors, possibly in the presence of faults, are forwarded to the fusion center that determines the final classification result. Classification fusion in our approach is implemented via error correcting codes to incorporate fault-tolerance capability. This new approach not only provides an improved fault-tolerance capability but also reduces computation time and memory requirements at the fusion center. Code matrix design is essential for the design of such systems. Two efficient code matrix design algorithms are proposed in this paper. The relative merits of both algorithms are also studied. We also develop sufficient conditions for asymptotic detection of the correct hypothesis by the proposed approach. Performance evaluation of the proposed approach in the presence of faults is provided. These results show significant improvement in fault-tolerance capability as compared with conventional parallel fusion networks.

Balanced-energy sleep scheduling scheme for high density cluster-based sensor networks

In order to conserve battery power in very dense sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. However, determining which of the sensor nodes should be put into the sleep state is non-trivial. As the goal of allowing nodes to sleep is to extend network lifetime, we propose and analyze a Balanced-energy Scheduling (BS) scheme in the context of cluster-based sensor networks. The BS scheme aims to evenly distribute the energy load of the sensing and communication tasks among all the nodes in the cluster, thereby extending the time until the cluster can no longer provide adequate sensing coverage. Two related sleep scheduling schemes, the Distance-based Scheduling (DS) scheme and the Randomized Scheduling (RS) scheme are also studied in terms of the coecien t of variation of their energy consumption. Analytical and simulation results are presented to evaluate the proposed BS scheme. It is shown that the BS scheme extends the cluster’s overall network lifetime signican tly while maintaining a similar sensing coverage compared with the DS and the RS schemes for sensor clusters.

Optimal Transmission Range for Wireless Ad Hoc Networks Based on Energy Efficiency

The transmission range that achieves the most economical use of energy in wireless ad hoc networks is studied for uniformly distributed network nodes. By assuming the existence of forwarding neighbors and the knowledge of their locations, the average per-hop packet progress for a transmission range that is universal for all nodes is derived. This progress is then used to identify the optimal per-hop transmission range that gives the maximal energy efficiency. Equipped with this analytical result, the relation between the most energy-economical transmission range and the node density, as well as the path-loss exponent, is numerically investigated. It is observed that when the path-loss exponent is high (such as four), the optimal transmission ranges are almost identical over the range of node densities that we studied. However, when the path-loss exponent is only two, the optimal transmission range decreases noticeably as the node density increases. Simulation results also confirm the optimality of the per-hop transmission range that we found analytically.