Advancing Data Privacy in Cloud Storage: A Novel Multi-Layer Encoding Framework - Kamta Nath Mishra; Rajesh Kumar Lal; Paras Nath Barwal; Alok Mishra (Applied Sciences, 2025)
Data privacy is a crucial concern for individuals using cloud storage services, and cloud service providers are increasingly focused on meeting this demand. However, privacy breaches in the ever-evolving cyber landscape remain a significant threat to cloud storage infrastructures. Previous studies have aimed to address this issue but have often lacked comprehensive coverage of privacy attributes. In response to the identified gap in privacy-preserving techniques for cloud computing, this research paper presents a novel and adaptable framework. This approach introduces a multi-layer encoding storage arrangement combined with the implementation of a one-time password authorization approach. By integrating these elements, the proposed approach aims to enhance both the flexibility and efficiency of data protection in cloud environments. The findings of this study are anticipated to have significant implications, contributing to the advancement of existing techniques and inspiring the development of innovative research-driven solutions. Continuous research efforts are required to validate the effectiveness of the proposed framework across diverse contexts and assess its performance against evolving privacy vulnerabilities in cloud computing.