An Access Control Model Against Attribute Guessing Attacks for Data Sharing in Cloud Computing Environment

ABSTRACT Data sharing is a fundamental component that facilitates collaboration and interoperability among entities in cloud computing environments. It enables cross‐domain access, concurrent task execution, and parallel multi‐task processing. However, challenges such as privacy breaches, vulnerabilities of sensitive data, and inflexible access control mechanisms are prevalent in data access scenarios. Many existing attribute‐based searchable encryption (ABSE) schemes suffer from issues like keyword leakage, limited query methods, and susceptibility to attribute guessing attacks. To address these challenges, this paper proposes an attribute‐based access control scheme designed to mitigate keyword‐guessing attacks in cloud environments. The proposed scheme has several advantages: (1) Enhanced Privacy Protection: By employing attribute‐based encryption (ABE), the scheme ensures user personal information and ciphertext attribute values remain protected during authentication through hidden attribute authentication techniques. (2) Resistance to Keyword‐Guessing Attacks: The scheme utilizes an anti‐guessing attribute encryption algorithm, ensuring that attribute keywords and access policies remain secure against guessing attacks during transmission. (3) A flexible ciphertext attribute search and matching algorithm enhances access control security and supports fine‐grained access control. This approach achieves precise, adaptable, and stealthy access control while strengthening privacy protection. It also accommodates diverse search requirements and ensures robust fine‐grained access control. Security analysis confirms its strong security. Performance analysis shows that it outperforms existing schemes.