Improved Cauchy Reed-Solomon Codes for Cloud Data Retrieval and Secured Data Storage using Role-Based Cryptographic Access and forensic investigation

Doling out client consent strategies to PC frameworks presents a huge test in guaranteeing legitimate approval, especially with the development of open frameworks and scattered stages like the cloud.  RBAC  has turned into a broadly involved strategy in cloud server applications because of its versatility. Granting access to cloud-stored data for investigating potential wrongdoings is crucial in computer forensic investigations. In cases where the cloud service provider's reliability is questionable, maintaining data confidentiality and establishing an efficient procedure for revoking access upon credential expiration is essential. As storage systems expand across vast networks, frequent component failures require stronger fault tolerance measures. Our work secure data-sharing system combines role (Authorized) based access control and AES encryption technology to provide safe key distribution and data sharing for dynamic groups. Data recovery entails protecting data dispersed over distributed systems by storing duplicate data and applying the erasure code technique. Erasure coding strategies, like Reed-Solomon codes, guarantee disc failure robustness while cutting down on data storage expenses dramatically. They do, however, also result in longer access times and more expensive repairs. Consequently, there has been a great deal of interest in academic and business circles for the investigation of novel coding strategies for cloud storage systems. The objective of this study is to present a novel coding method that utilizes the intricate Cauchy matrix in order to improve Reed-Solomon coding efficiency and strengthen fault tolerance

Enhanced Cauchy Matrix Reed-Solomon Codes and Role-Based Cryptographic Data Access for Data Recovery and Security in Cloud Environment

In computer systems ensuring proper authorization is a significant challenge, particularly with the rise of open systems and dispersed platforms like the cloud. Role-Based Access Control (RBAC) has been widely adopted in cloud server applications due to its popularity and versatility. When granting authorization access to data stored in the cloud for collecting evidence against offenders, computer forensic investigations play a crucial role. As cloud service providers may not always be reliable, data confidentiality should be ensured within the system. Additionally, a proper revocation procedure is essential for managing users whose credentials have expired.  With the increasing scale and distribution of storage systems, component failures have become more common, making fault tolerance a critical concern. In response to this, a secure data-sharing system has been developed, enabling secure key distribution and data sharing for dynamic groups using role-based access control and AES encryption technology. Data recovery involves storing duplicate data to withstand a certain level of data loss. To secure data across distributed systems, the erasure code method is employed. Erasure coding techniques, such as Reed-Solomon codes, have the potential to significantly reduce data storage costs while maintaining resilience against disk failures. In light of this, there is a growing interest from academia and the corporate world in developing innovative coding techniques for cloud storage systems. The research goal is to create a new coding scheme that enhances the efficiency of Reed-Solomon coding using the sophisticated Cauchy matrix to achieve fault toleranc