Cover
Vol. 20 No. 1 (2024)

Published: June 30, 2024

Pages: 68-77

Original Article

Improving Performance of Searchable Symmetric Encryption Through New Information Retrieval Scheme

Aya A. Alyousif 1 Ali A. Yassin
1Department of Computer science, Education College for Pure Sciences, University of Basrah, Basrah, 61004, Iraq
History
  • Received: March 15, 2023
  • Revised: May 6, 2023
  • Accepted: May 12, 2023
  • Available Online: October 31, 2023
DOI

https://doi.org/10.37917/ijeee.20.1.7

Abstract

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.

Keywords

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