Optimised compact authentication scheme based on three factors for cloud-based electronic transactions

Cloud services provide seamless data sharing, storage, and processing, enabling for the development of scalable applications and services capable of responding to real-time events. But as cloud technology becomes more common in daily life, it presents serious security risks, especially in relation to data breaches, illegal access, and complying with regulations standards. In order to increase the security of cloud-based electronic transactions, this study proposes a novel multi-factor authentication framework. In order to detect intrusions and reject malicious data before it is stored, the proposed approach incorporates an adaptive neuro-fuzzy inference system (ANFIS). Furthermore, sensitive user data, such as credentials and biometric information, is protected with homomorphic encryption (HE) for enhanced privacy. The framework for security is constructed with an optimised compact authentication (OCA) scheme that consists of three phases: setup, registration, and authentication. The system solves important vulnerabilities such session key leakage and provides procedures for user revocation and re-registration. The model performs significantly better than existing security methods when evaluated using throughput, latency and packet loss ratio. The Python platform is used to develop and test the complete system, proving its efficacy in boosting trust among users in cloud services and protecting electronic transactions conducted in the cloud.