Abstract
Outsourcing data/computation intensive tasks to servers having great computing power and data analytics skills is gaining popularity. While this outsourcing model, due to its cost efficiency, has been widely used by numerous clients, making sure that loss of privacy and integrity of results are not affected remain as challenges, especially in public cloud infrastructure. For addressing these challenges, clients must outsource their data in a privacy-preserving and verifiable manner. The cost of assuring both privacy of data and correctness of results must impose cost marginally less than the cost of actual computation. In this paper, we address the problem of secure outsourcing of Closest Pair of Points computation. Finding Closest Pair of Points is central to many complex applications like clustering. Our scheme involves the client sending encrypted points to the server and receiving the result which is a pair of points (with smallest distance between them) along with a proof of correctness. Data encryption done to ensure privacy of input points must be such that the encrypted points retain the same order as the original points. For this, we designed and used a novel encryption scheme which is additively homomorphic and order-preserving for encrypting input points in our protocol. The protocol requires the server to compute almost all distances to be able to provide the proof of it having computed the results honestly.
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Kuruba, C., Gilbert, K., Sidhaye, P., Pareek, G., Rangappa, P.B. (2016). Outsource-Secured Calculation of Closest Pair of Points. In: Mueller, P., Thampi, S., Alam Bhuiyan, M., Ko, R., Doss, R., Alcaraz Calero, J. (eds) Security in Computing and Communications. SSCC 2016. Communications in Computer and Information Science, vol 625. Springer, Singapore. https://doi.org/10.1007/978-981-10-2738-3_33
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DOI: https://doi.org/10.1007/978-981-10-2738-3_33
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