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Frequency-hiding order-preserving encryption (FH-OPE) has emerged as an important tool in data security, particularly in cloud computing, because of its unique ability to preserve the order of plaintexts in their corresponding ciphertexts and enable efficient range queries on encrypted data. Despite its strong security model, indistinguishability under frequency analyzing ordered chosen plaintext attack (IND-FA-OCPA), our research identifies a vulnerability in its design, particularly the impact of range queries. In our research, we quantify the frequency of data exposure resulting from these range queries and present potential inference attacks on the FH-OPE scheme. Our findings are substantiated through experiments on real-world datasets, with the goal of measuring the frequency of data exposure resulting from range queries on FH-OPE encrypted databases. These results quantify the level of risk in practical applications of FH-OPE and reveal the potential for additional inference attacks and the urgency of addressing these threats. Consequently, our research highlights the need for a more comprehensive security model that considers the potential risks associated with range queries and underscores the importance of developing new range-query methods that prevent exposing these vulnerabilities.
Yang et al. (Thu,) studied this question.