A Dynamic Multi-Factor Authentication and RLWE-Based Spatio- Temporal Mechanism for Securing Big Data Storage in Cloud

Abstract

Background Information: The increasing demand for cloud-based big data storage necessitates strong security. This paper presents a novel Dynamic Multi-Factor Authentication (DMFA) and Ring Learning With Errors (RLWE)-Based Spatio-Temporal Mechanism that ensures secure encryption, adaptive authentication, and real-time access control. Thus, the overall framework enhances the security, confidentiality, and reliability of access to the data against continuously evolving cyber threats. Objectives: With integration of DMFA and RLWE-based cryptosystems to strengthen data safety in cloud based big data stores. The focus lies on the minimalization of unintended access, with enhancing key management features, dynamic authenticity, and quality enforcement of spatiotemporal security policies through improving the risks relating to data leaks and cyber- crimes. Methods: Mechanism proposed: the mechanism proposed has the integration of quantum- resistant security through RLWE-based encryption, coupled with DMFA adaptive authentication. It also allows data coming from analytics with regards to devices, behavior, and  ocation for dynamically adjusting permissions pertaining to accesses; hence, a spatio-temporalrisk model that enables data access control with real-time mitigation in cloud storage. Empirical Results: The framework attains 97.8% authentication accuracy, reduces unauthorized access attempts by 46%, and enhances the efficiency of encrypting data by 38% compared to the traditional models. Results demonstrate improvement in security, performance, and resilience in cloud-based big data storage environments. Conclusion: DMFA with RLWE-based encryption makes cloud data highly secure through confidentiality, dynamic access control, and strong authentication. The future improvements
are on blockchain-based logging, AI-driven anomaly detection, and post-quantum cryptographic techniques for securing the cloud storage system further.