Dynamic Searchable Encryption (DSE) has emerged as a solution to efficiently handle and protect large-scale data storage in encrypted databases (EDBs). Volume leakage poses a significant threat, as it enables adversaries to reconstruct search queries and potentially compromise the security and privacy of data. Padding strategies are common countermeasures for the leakage, but they significantly increase storage and communication costs. In this work, we develop a new perspective to handle volume leakage. We start with distinct search and further explore a new concept called \textit{distinct} DSE (\textit{d}-DSE). We also define new security notions, in particular Distinct with Volume-Hiding security, as well as forward and backward privacy, for the new concept. Based on \textit{d}-DSE, we construct the \textit{d}-DSE designed EDB with related constructions for distinct keyword (d-KW-\textit{d}DSE), keyword (KW-\textit{d}DSE), and join queries (JOIN-\textit{d}DSE) and update queries in encrypted databases. We instantiate a concrete scheme \textsf{BF-SRE}, employing Symmetric Revocable Encryption. We conduct extensive experiments on real-world datasets, such as Crime, Wikipedia, and Enron, for performance evaluation. The results demonstrate that our scheme is practical in data search and with comparable computational performance to the SOTA DSE scheme (\textsf{MITRA}*, \textsf{AURA}) and padding strategies (\textsf{SEAL}, \textsf{ShieldDB}). Furthermore, our proposal sharply reduces the communication cost as compared to padding strategies, with roughly 6.36 to 53.14x advantage for search queries.

翻译：动态可搜索加密（DSE）已成为在加密数据库（EDB）中高效处理和保护大规模数据存储的解决方案。体积泄露构成重大威胁，因为它使攻击者能够重建搜索查询，并可能危及数据的安全性和隐私性。填充策略是应对这种泄露的常见对策，但会显著增加存储和通信成本。本研究从新视角处理体积泄露问题。我们从差异化搜索入手，进一步探索了名为"差异化DSE"（d-DSE）的新概念。我们还为该新概念定义了新的安全概念，特别是具有体积隐藏安全性的差异化概念，以及前向和后向隐私。基于d-DSE，我们构建了针对差异化关键字（d-KW-dDSE）、关键字（KW-dDSE）和连接查询（JOIN-dDSE）以及加密数据库中更新查询的相关构造所设计的EDB。我们采用对称可撤销加密实例化了一个具体方案BF-SRE。我们在真实数据集（如Crime、Wikipedia和Enron）上进行了广泛实验以评估性能。结果表明，我们的方案在数据搜索方面具有实用性，且计算性能与最先进的DSE方案（MITRA*、AURA）和填充策略（SEAL、ShieldDB）相当。此外，与填充策略相比，我们的方案大幅降低了通信成本，搜索查询的优势约为6.36至53.14倍。