Abstract Cloud computing offers unparalleled flexibility and scalability, but introduces critical security challenges, particularly in dynamically distributed environments. This paper presents CAEM-ESAC, a novel context-aware encryption model designed to revolutionize cloud security by incorporating contextual factors, such as user identity, location, access time, and device characteristics, into encryption and decryption processes. Unlike traditional encryption methods that rely on static protocols, CAEM-ESAC dynamically adjusts encryption parameters based on the evolving context of data access, ensuring a more responsive and secure system. The model employs an advanced methodology combining context-based analysis, adaptive encryption algorithms, and dynamic access control policies, offering a multilayered defense strategy. Through extensive simulation-based analysis and theoretical security proofs, the results demonstrate that CAEM-ESAC significantly enhances data confidentiality, integrity, and access control in cloud environments. By continuously optimizing encryption according to environmental conditions, CAEM-ESAC is shown to be more resilient against sophisticated attacks and emerging security threats. Furthermore, the model improves the scalability and adaptability of cloud security systems by mitigating the weaknesses of conventional encryption methods, particularly in highly dynamic and decentralized infrastructures. These findings open new avenues for secure cloud computing, where encryption is no longer a static process but an adaptive, context-driven solution. CAEM-ESAC offers a forward-looking framework that addresses the growing demands of cloud security, establishing a foundation for future advancements in secure, context-aware encryption technologies.
Alsirhani et al. (Wed,) studied this question.