BloomSec: Scalable and privacy-preserving searchable encryption for cloud environments

Abstract

The utilization of on-demand remote cloud services provides a flexible way to fulfill the demands of emerging resource-intensive applications. However, migrating data to the cloud also introduced security threats, including unauthorized access and information theft. To resolve this issue, the existing solutions encrypt information locally before uploading it to the server. This process provides information protection with the limitation of non-searchable data. To overcome this limitation, searchable encryption has emerged as a promising cryptographic technique. Some existing searchable encryption techniques are facing data leakage issues by exposing search queries or data to the cloud service provider. Another class of existing searchable schemes introduces processing cost or communication overhead for the data user. The recent searchable solution that is both secure and efficient for data users is Labeled Searchable Encryption (LSE). However, LSE cannot manage large datasets effectively and introduces communication overhead on the data user side. To ensure that Secure Searchable Encryption (SSE) can meet the demands of modern data-driven applications without compromising security and performance, this study aims to investigate and develop novel approaches to enhance the efficiency and security of SSE for large datasets. Experimental findings have proved that the proposed BloomSec is much more efficient and scalable than the classic method of Labeled Searchable Encryption (LSE), consuming significantly less overhead for users, which makes it practically useful for a large dataset without compromising security.