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Title: An energy-efficient data aggregation scheme with privacy and integrity in wireless sensor networks
Authors: Bista, Rabindra
Keywords: Wireless sensor networks
Data aggregation
Privacy and integrity preservation
Issue Date: 9-Nov-2017
Abstract: Wireless sensor networks (WSNs) were originally adopted by military applications, and are becoming integral part of more and more civilian applications to improve quality of life. With current wireless sensor network technology, people gain advanced knowledge of physical and social systems, opening the advent of ubiquitous sensing era. In-network processing i.e., data aggregation is an essential function of WSNs to collect raw sensory data and to get aggregated statistics about the measured environment helping queriers capture the major feature or changes of the measured systems. As more applications of WSNs collect sensitive measurements of people’s everyday life, privacy and security concerns draw more attention. Since WSNs are resources-constrained (i.e., limited power supply, low bandwidth and so on), it is very essential to efficiently gather data from the WSNs for making their life prolonged. Data aggregation can conserve a significant amount of energy by minimizing transmission cost in terms of the number of data packets. A usual concept to collect data in a sink node is to transfer data from other sensor nodes to the node by multi-hop. However, it gives rise to two problems. One is the hotspot problem, in which the particular sensor nodes (core nodes) in the network run out of energy sooner than other nodes. As a result, the network loses its service ability, regardless of a large amount of residual energy of the other nodes. The other is that the network generates unnecessary traffic during data transmission for choosing a proper data sending path. Aggregated result of sensor data at the sink node is used for making important decisions. Because WSNs are not always reliable, it cannot be expected that all nodes reply to all request. Therefore, the final aggregated result need to be properly derived. For this, the information of the sensor nodes (Node Identifications, IDs) contributing to the final aggregated result must be known by the sink node. The communication cost of transmitting IDs of all contributed sensor nodes along with the aggregated data must also be minimized. However, the existing work is limited to transmit a few IDs of sensor nodes due to limited bandwidth. Moreover, many applications require privacy and integrity protection of the sampled data while they travel from the source sensor nodes to the sink node. If privacy of sensory content is not preserved, it is not feasible to deploy the WSNs for information collection. On the other hand, if integrity of the collected sensory information is not protected, no queriers or users can trust and/or use the collected information. Hence, two important issues should be addressed before wireless sensor network systems can realize their promise in civilian applications: (1) protecting data privacy, so that the deployment of the wireless sensor network systems is feasible; (2) enforcing integrity, so that users can trust the collected information (or aggregated result). Existing schemes suffering from high communication cost, high computation cost and data propagation delay are the obstacles in realizing the promises. This dissertation explores efficient data aggregation, node-ID transmission mechanism, and privacy and integrity of data aggregation in wireless sensor networks. First, we propose a new energy-efficient data aggregation scheme for WSNs, called Designated Path (DP) scheme. In the DP scheme, a set of paths is predetermined and run the paths in a round-robin fashion so that all the nodes can participate equally in the workload of gathering and transferring data to the sink. It has the advantage of incurring less communication overhead for the aggregation. Next, for supporting scalable node ID transmission, we propose a novel mechanism in which a special set (i.e., 2n type) of real numbers are assigned to sensor nodes as their IDs so that a single bit is sufficient to hold ID of a sensor node during transmission of aggregated data to the sink node. For this, we, first, generate fixed size signatures for the IDs of all sensor nodes and then superimpose the signatures during data aggregation phase. We named this mechanism as signature scheme which has the advantage of incurring less communication and computation overheads while transmitting IDs of sensor nodes. Finally, we address both privacy of individual sensory data and integrity of aggregation result simultaneously. It is very challenging to achieve the synergy of privacy and integrity at the same time, because privacy-preserving schemes try to hide or interfere with data, while integrity protection is usually necessitated to enable peer monitoring or public access of the data. Therefore, they can be the conflicting requirements, one barricading the implementation of the other. We propose a new and efficient privacy and integrity preserving scheme for WSNs. Our scheme makes use of complex number, which is an algebraic expression using arithmetic operations, such as addition (+), to aggregate and hide data (for data privacy) from other sensor nodes and adversaries during transmissions to the data sink. In our scheme, the real unit of a complex number is used for concealing sampled data whereas the imaginary unit is exploited for providing data integrity checking. It has the advantage of incurring less computation and communication overheads, low data propagation delay, and high level of data integrity for privacy and integrity preserving data aggregation. To show the efficacy and efficiency of the proposed schemes, we first numerically analyze the proposed DP scheme, signature scheme and privacy and integrity preserving scheme. Next, we present analytic performance evaluation and simulation results of our schemes by comparing them with other existing schemes: the performance of DP scheme with Directed-Diffusion (DD) and Hierarchical Data Aggregation (HDA), signature scheme with CMT scheme, and privacy and integrity preserving scheme with Integrity-enforcing Cluster-based Private Data Aggregation (iCPDA) and Integrity-Protecting Data Aggregation (iPDA). The evaluations show that our proposed schemes are much more efficient than the respective existing schemes.
Description: A dissertation submitted to the graduate school in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Engineering, Graduate School of Chonbuk National University, 2011.
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