查看文章

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 …