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Secure nearest neighbor revisited

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TLDR
New SNN methods are designed, which provide customizable tradeoff between efficiency and communication cost, and are as secure as the encryption scheme E used to encrypt the query and the database, where E can be any well-established encryption schemes.
Abstract
In this paper, we investigate the secure nearest neighbor (SNN) problem, in which a client issues an encrypted query point E(q) to a cloud service provider and asks for an encrypted data point in E(D) (the encrypted database) that is closest to the query point, without allowing the server to learn the plaintexts of the data or the query (and its result). We show that efficient attacks exist for existing SNN methods [21], [15], even though they were claimed to be secure in standard security models (such as indistinguishability under chosen plaintext or ciphertext attacks). We also establish a relationship between the SNN problem and the order-preserving encryption (OPE) problem from the cryptography field [6], [5], and we show that SNN is at least as hard as OPE. Since it is impossible to construct secure OPE schemes in standard security models [6], [5], our results imply that one cannot expect to find the exact (encrypted) nearest neighbor based on only E(q) and E(D). Given this hardness result, we design new SNN methods by asking the server, given only E(q) and E(D), to return a relevant (encrypted) partition E(G) from E(D) (i.e., G ⊆ D), such that that E(G) is guaranteed to contain the answer for the SNN query. Our methods provide customizable tradeoff between efficiency and communication cost, and they are as secure as the encryption scheme E used to encrypt the query and the database, where E can be any well-established encryption schemes.

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Citations
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Journal ArticleDOI

Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement

TL;DR: A new method of keyword transformation based on the uni-gram is developed, which will simultaneously improve the accuracy and creates the ability to handle other spelling mistakes and consider the keyword weight when selecting an adequate matching file set.
Proceedings ArticleDOI

Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking

TL;DR: This paper presents a verifiable privacy-preserving multi-keyword text search (MTS) scheme with similarity-based ranking to address the problem of secure search functions over encrypted data and proposes two secure index schemes to meet the stringent privacy requirements under strong threat models.
Journal ArticleDOI

A framework for protecting worker location privacy in spatial crowdsourcing

TL;DR: This paper argues that existing location privacy techniques are not sufficient for SC, and a mechanism based on differential privacy and geocasting that achieves effective SC services while offering privacy guarantees to workers is proposed.
Proceedings ArticleDOI

Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud

TL;DR: This paper proposes a novel multi-keyword fuzzy search scheme that achieves fuzzy matching through algorithmic design rather than expanding the index file and effectively supports multiple keyword fuzzy search without increasing the index or search complexity.
Proceedings ArticleDOI

Secure k-nearest neighbor query over encrypted data in outsourced environments

TL;DR: Wang et al. as discussed by the authors proposed a secure kNN protocol that protects the confidentiality of the data, user's input query, and data access patterns, and empirically analyzed the efficiency of their protocols through various experiments.
References
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Proceedings ArticleDOI

Executing SQL over encrypted data in the database-service-provider model

TL;DR: The paper explores an algebraic framework to split the query to minimize the computation at the client site, and explores techniques to execute SQL queries over encrypted data.
Proceedings ArticleDOI

Order preserving encryption for numeric data

TL;DR: This work presents an order-preserving encryption scheme for numeric data that allows any comparison operation to be directly applied on encrypted data, and is robust against estimation of the true value in such environments.
Proceedings ArticleDOI

The new Casper: query processing for location services without compromising privacy

TL;DR: Zhang et al. as mentioned in this paper presented Casper1, a new framework in which mobile and stationary users can entertain location-based services without revealing their location information, which consists of two main components, the location anonymizer and the privacy-aware query processor.
Book ChapterDOI

Order-Preserving Symmetric Encryption

TL;DR: The notion of order-preserving symmetric encryption (OPE) was introduced by Agrawal et al. as mentioned in this paper, who showed that a straightforward relaxation of standard security notions for encryption such as indistinguishability against chosen-plaintext attack (IND-CPA) is unachievable by a practical OPE scheme.
Proceedings ArticleDOI

Private queries in location based services: anonymizers are not necessary

TL;DR: This work proposes a novel framework to support private location-dependent queries, based on the theoretical work on Private Information Retrieval (PIR), which achieves stronger privacy for snapshots of user locations and is the first to provide provable privacy guarantees against correlation attacks.