DOI: 10.1155/jece/4832818 ISSN: 2090-0147

Hybrid Advanced Encryption Standard–Rivest–Shamir–Adleman‐Based Mutual Authentication Model for the Secure Access Control Scheme in Decentralized Storage Systems

Abhijeet Cholke, V. V. Mandhare, P. S. Vikhe, Swati Bhavsar

In decentralized storage systems, the authentication model relies on user identity verification and grants only authorized data access. Problems include scalability in the case of the number of users and data sharing, security, which prevents data breaches, and privacy, which prevents personal data disclosure. Therefore, due to the weaknesses of the existing models, a new hybrid model—hybrid advanced encryption standard (AES)‐–Rivest–Shamir–Adleman (RSA)‐based mutual authentication mechanism (HARSM) is developed, which is based on a two‐way mutual authentication model for decentralized storage systems. The research provides distinct contributions in two main categories. Firstly, it suggests a groundbreaking key setup algorithm that combines the powerful security of RSA while maintaining the efficiency of AES, thus leading to a hybrid encryption scheme. This approach utilizes RSA for providing secure key exchange and AES for data encryption in bulk, which improves the security and efficiency of data protection in decentralized storage systems. Next, the research discovers a new mutual authentication procedure after the matching process, in which the data owner validates the link between the data user and the blockchain. This mutual authentication step is a way of strengthening data access security as it verifies the identity and access privileges of the user, and this, in turn, safeguards against unauthorized access and data breaches. Experimental analysis shows that with 250 users, the models demonstrate significant improvements in privacy ratio, encryption time, gas usage, decryption time, information loss, memory usage, and transaction time, with scores of 1.44, 0.35 ms, 120.56 kB, 0.025 ms, 0.12, 214.63 kB, and 0.51 ms without attack for the Students Marksheet dataset, respectively, when compared to the existing models.

More from our Archive