A Secured and Lightweight Document Handling Procedure Using Blockchain Assisted Decentralized Data Manipulation Strategy - T, Geetha; G, Sowmiya; M, Priscilla; J, Jayanthi; S P, Raut; Kanan, Mohammad (2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), 2024)
Managing data encompasses gathering, analyzing, storing and disseminating information. These days, multi-partner firms can't function without data sharing and collaborative data processing, which are essential for finding fresh insights. The majority of the time, institutions share data for institutional decision-making, advertising, and marketing purposes. The problem is that organizations share the data obtained, which mostly concerns individuals called data subjects or producers, without obtaining their meaningful consent. This means that those whose data is being used or misused have no idea what's going on. Data subjects also have little control over who outside organizations can access their information. In this work, we argued that data management should aim to gain the confidence of people whose information is being processed. Data subjects should be able to access and understand their data in order to do this. Lightweight Decentralized Data Manipulation Strategy (LDDMS) is a cloud-based data management and sharing platform that allows data subjects to choose who may access their data and consent to its collection and utilization using smart contracts. In order to determine how effective the suggested method is, it is cross-validated with the standard document processing technique known as Intelligent File Handling System (IFHS). Database mismatches are a common problem, but this method fixes them. The reliability and accuracy of data management are greatly enhanced by our system's exceptional performance in critical areas including data security, information verification, and error traceback. We provide a robust LDDMS as a future-proof answer to the problem of safe and effective educational data management.