A Robust Dynamic Searchable Encryption Framework Supporting Secondary Confirmation for Secure Cloud Environments
Jiayang Gao, Zuobin Ying · 2025
Dynamic searchable encryption (DSE) systems ensure data privacy in cloud and distributed environments. However, existing DSE solutions often suffer from false positives in Bloom filters, which compromise query accuracy and degrade system performance during data updates. We propose a secondary confirmation mechanism leveraging the Error-Resilient Cuckoo Filter (ERCF) to address this limitation. This mechanism revalidates the data flagged by Bloom filters, effectively mitigating the impact of false positives and ensuring accurate query results. Integrating ERCF significantly enhances the system’s robustness, enabling it to maintain consistent performance even when processing large-scale, complex, and dynamic datasets. Extensive experiments on diverse and large-scale datasets demonstrate the efficacy of our approach in improving query precision and maintaining data consistency. This method provides a practical and innovative solution for advancing DSE systems, particularly in challenging scenarios requiring high reliability and efficiency.