Secure data aggregation

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Abstract

Chapter 4 considered a general WSN security problem. In this chapter we want to focus on a specific WSN service: The data collection. If each single node sends its own data to the collecting point in an independent way this will result in a huge waste of energy. To meet the severe energy constraints in WSNs, some researchers have proposed to use the in-network data aggregation technique (i.e., combining partial results at intermediate nodes during message routing), which significantly reduces the communication overhead. Some researchers also proposed algorithms to securely compute a fewaggregates, such asSum(the sum of the sensed values), Count (number of nodes) and Average. However, to the best of our knowledge, there is no prior work which securely computes the Median, although the Median is considered to be an important aggregate. The contribution of this chapter is twofold. We first propose a protocol to compute an approximate Median and verify if it has been falsified by an adversary. Then, we design an attack-resilient algorithm to compute the Median even in the presence of a few compromised nodes. We evaluate the performance and cost of our approach via both analysis and simulation. Our results show that our approach is scalable and efficient.

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APA

Secure data aggregation. (2016). In Advances in Information Security (Vol. 65, pp. 101–124). Springer New York LLC. https://doi.org/10.1007/978-1-4939-3460-7_5

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