Stateful Order-Preserving Encryption for Secure Cloud Databases

We propose stateful order-preserving encryption (SOPE), a novel framework designed to realize human-centric data security and privacy, the fundamental values of the Fifth Industrial Revolution. Conventional order-preserving encryption supports efficient queries in cloud databases but fundamentally leaks plaintext distributions, leaving data vulnerable to inference attacks. To mitigate this vulnerability while maintaining query efficiency, SOPE introduces a partition-based dynamic density adjustment mechanism under an honest-but-curious threat model. This mechanism offsets density imbalances between partitions in real time by inserting decoy ciphertexts, thereby limiting the leakage scope to the order of data while obscuring frequency information. Our analysis and empirical evaluations demonstrate that SOPE’s ciphertexts consistently approach a uniform distribution by adaptively compensating for the underlying plaintext distribution through decoy insertion. While the continuous insertion of decoy ciphertexts inevitably incurs additional storage overhead (controlled by a tunable parameter λ), our evaluations demonstrate practical performance. By striking an optimal balance between efficiency and human privacy rights, SOPE provides a trustworthy infrastructure for secure data utilization.