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Enabling efficient approximate nearest neighbor search for outsourced database in cloud computing
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DOI：10.1007/s00500-015-1758-6.png)
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Approximate nearest neighbor (ANN) search in high-dimensional space has been studied extensively in recent years. However, it supports only ANN search over plaintext in traditional locality-sensitive hashing (LSH). How to perform ANN search over encrypted data becomes a new challenging task. In this paper, we make an attempt to formally address the problem. We propose a new secure and efficient ANN search scheme over encrypted data based on SortingKeys-LSH (SK-LSH) and mutable order-preserving encryption (mOPE). In our construction, a secure index is generated by incorporating SK-LSH with mOPE, which can simultaneously achieve efficient ANN search and ensure data confidentiality. Furthermore, the proposed solution can achieve efficient range query on encrypted data. Security analysis demonstrates that our construction can achieve the desired security properties.
Keyword:
Approximate nearest neighbor
Locality sensitive hashing
Order-preserving encryption
Outsourced database
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