Searchable symmetric encryption (SSE) is a robust cryptographic method that allows users to store and retrieve encrypted data on a remote server, such as a cloud server, while maintaining the privacy of the user’s data. The technique employs symmetric encryption, which utilizes a single secret key for both data encryption and decryption. However, extensive research in this field has revealed that SSE encounters performance issues when dealing with large databases. Upon further investigation, it has become apparent that the issue is due to poor locality, necessitating that the cloud server access multiple memory locations for a single query. Additionally, prior endeavors in this domain centered on locality optimization have often led to expanded storage requirements (the stored encrypted index should not be substantially larger than the original index) or diminished data retrieval efficiency (only required data should be retrieved).we present a simple, secure, searchable, and cost-effective scheme, which addresses the aforementioned problems while achieving a significant improvement in information retrieval performance through site optimization by changing the encrypted inverted index storage mechanism. The proposed scheme has the optimal locality O(1) and the best read efficiency O(1)with no significant negative impact on the storage space, which often increases due to the improvement of the locality. Using real-world data, we demonstrate that our scheme is secure, practical, and highly accurate. Furthermore, our proposed work can resist well-known attacks such as keyword guessing attacks and frequency analysis attacks.
Searchable symmetric encryption (SSE) enables clients to outsource their encrypted documents into a remote server and allows them to search the outsourced data efficiently without violating the privacy of the documents and search queries. Dynamic SSE schemes (DSSE) include performing update queries, where documents can be added or removed at the expense of leaking more information to the server. Two important privacy notions are addressed in DSSE schemes: forward and backward privacy. The first one prevents associating the newly added documents with previously issued search queries. While the second one ensures that the deleted documents cannot be linked with subsequent search queries. Backward has three formal types of leakage ordered from strong to weak security: Type-I, Type-II, and Type-III. In this paper, we propose a new DSSE scheme that achieves Type-II backward and forward privacy by generating fresh keys for each search query and preventing the server from learning the underlying operation (del or add) included in update query. Our scheme improves I/O performance and search cost. We implement our scheme and compare its efficiency against the most efficient backward privacy DSSE schemes in the literature of the same leakage: MITRA and MITRA*. Results show that our scheme outperforms the previous schemes in terms of efficiency in dynamic environments. In our experiments, the server takes 699ms to search and return (100,000) results.