A Secure and Efficient KA-PRE Scheme for Data Transmission in Remote Data Management Environments
Year: 2025
Type: article
Abstract: In recent years, remote data management environments have been increasingly deployed across diverse infrastructures, accompanied by a rapid surge in the demand for sharing and collaborative processing of sensitive data. Consequently, ensuring data security and privacy protection remains a fundamental challenge. A representative example of such an environment is the cloud, where efficient mechanisms for secure data sharing and access control are essential. In domains such as finance, healthcare, and public administration, where large volumes of sensitive information are processed by multiple participants, traditional access-control techniques often fail to satisfy the stringent security requirements. To address these limitations, Key-Aggregate Proxy Re-Encryption (KA-PRE) has emerged as a promising cryptographic primitive that simultaneously provides efficient key management and flexible authorization. However, existing KA-PRE constructions still suffer from several inherent security weaknesses, including aggregate-key leakage, ciphertext insertion and regeneration attacks, metadata exposure, and the lack of participant anonymity within the data-management framework. To overcome these limitations, this study systematically analyzes potential attack models in the KA-PRE setting and introduces a novel KA-PRE scheme designed to mitigate the identified vulnerabilities. Furthermore, through theoretical comparison with existing approaches and an evaluation of computational efficiency, the proposed scheme is shown to enhance security while maintaining practical performance and scalability.
Source: Electronics
Authors: JaeJeong Shin, Deok Gyu Lee, Daehee Seo, Wonbin Kim, Su-Hyun Kim
Institutions: Soonchunhyang University, Seowon University, Sangmyung University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4415930240
