Privacy-preserving Information Retrieval Research Articles

Privacy-preserving continuous authentication using behavioral biometrics

Continuous authentication modalities collect and utilize users’ sensitive data to authenticate them continuously. Such data contain information about user activities, behaviors, and other demographic information, which causes privacy concerns. In this paper, we propose two privacy-preserving protocols that enable continuous authentication while preventing the disclosure of user-sensitive information to an authentication server. We utilize homomorphic cryptographic primitives that protect the privacy of biometric features with an oblivious transfer protocol that enables privacy-preserving information retrieval. We performed the biometric evaluation of the proposed protocols on two datasets, a swipe gesture dataset and a keystroke dynamics dataset. The biometric evaluation shows that the protocols have very good performance. The execution time of the protocols is measured by considering continuous authentication using: only swipe gestures, keystroke dynamics, and hybrid modalities. The execution time proves the protocols are very efficient, even on high-security levels.

Proxy-Terms Based Query Obfuscation Technique for Private Web Search

Search engines store users’ queries in a query log for performing personalized information retrieval. However, query logs cause privacy concerns and reveal a lot of information about individuals if used against them. Private web search (PWS) provides a privacy-preserving information retrieval (IR) facility which allows users to retrieve information from an IR system without revealing true search queries. Current PWS techniques that are explored in the domain of web search are query obfuscation-based private web search (OB-PWS). These techniques achieve web privacy by injecting cover queries into the user profiles. However, existing OB-PWS techniques submit true queries along with cover queries and achieve query obfuscation in an isolated manner without considering the similarity between consecutive queries. In this article, we propose a proxy-terms based query obfuscation technique that allows users to retrieve information from an IR system through proxy queries without submitting true queries. IR system automatically generates cover queries and true queries from the proxy queries and cannot differentiate whether the user is trying to retrieve information for the cover queries or true query. We analyzed the effectiveness of the proposed technique on test queries, and develop a similarity metric for testing the accuracy of the proposed technique. Promising results of experiments confirm the effectiveness of the proposed technique.

A novel recursive privacy-preserving information retrieval approach for private retrieval

A novel recursive privacy-preserving information retrieval approach for private retrieval

A secure heuristic semantic searching scheme with blockchain-based verification

Secure semantic searching provides privacy-preserving information retrieval for arbitrary queries semantically related to keywords. However, current verification mechanisms cannot verify the correctness of search results for semantically related queries in mutual distrust scenarios. Moreover, most secure semantic searching schemes still perform exact matching on ciphertext after query expansion, then directly accumulate the weights of the matched keywords as similarity measurements to rank the documents, resulting in the search results with unsatisfied ranking. In this paper, we propose a secure heuristic semantic searching scheme, in which a privacy-preserving word nonlinear matching (PPWNM) method is developed, and a blockchain-based verification is designed to obtain trustworthy search results with high retrieval accuracy. Specifically, we describe several retrieval heuristics and formulate them as a word nonlinear matching problem, then transform it to the PPWNM problem for calculating the similarity measurement between the query and document so that the highly accurate ranked results can be obtained. Also we design a blockchain-based verification mechanism in which the blockchain nodes utilize the proofs generated during the matching process to verify the correctness of the search results and reach a consensus to ensure the trustworthy results and fair payment between the participants in a mutual distrust model. Our security analysis and experimental results show that the proposed scheme is secure and has higher accuracy compared with the existing other schemes.

A novel recursive privacy-preserving information retrieval approach for private retrieval

A novel recursive privacy-preserving information retrieval approach for private retrieval