Outsourcing of Secure k-Nearest Neighbours Interpolation Method

• Published in: International journal of advanced computer science & applications Vol. 9; no. 4
• Main Authors: Kalideen, Muhammad Rifthy, Tugrul, Bulent
• Format: Journal Article
• Language: English
• Published: West Yorkshire Science and Information (SAI) Organization Limited 2018
• Subjects: Algorithms; Cloud computing; Interpolation; Privacy; Queries
• ISSN: 2158-107X; 2156-5570
• DOI: 10.14569/IJACSA.2018.090446

Cloud computing becomes essential in these days for the enterprises. Most of the large companies are moving their services and data to the cloud servers which offer flexibility and efficiency. Data owner (DO) hires a cloud service provider (CSP) to store its data and carry out the related computation. The query owner (QO) sends a request which is crucial for its future plans to the CSP. The CSP computes all necessary calculations and returns the result back to the QO. Neither the data nor query owners want to reveal their private data to anyone. k-Nearest Neighbour (k-NN) interpolation is one of the essential algorithms to produce a prediction value for an unmeasured location. Simply, it finds k number of nearest neighbours around the query point to produce an output. Oblivious RAM (ORAM) has been used to protect the privacy in cloud computing. In our work, we will perform the k-NN method using the kd-tree and ORAM without revealing both the data-owner’s and query owner’s confidential data to each other or to third parties. The proposed solution will be analysed to ensure that it provides accurate and reliable predictions while preserving the privacy of all parties.