An adaptive learning model for secure data sharing in decentralized environments using blockchain technology
Year: 2025
Type: article
Abstract: Blockchain technology has rapidly emerged as a vital skillset, reshaping digital infrastructure with its decentralized, transparent, and secure characteristics. These core features have driven its integration across various industrial applications, establishing it as a foundation for modern computing paradigms such as cloud and edge computing. Recognizing this potential, the present study introduces a novel and disruptive approach utilizing an adaptive learning model to enhance security within data-sharing ecosystems through decentralized access control mechanisms. The proposed framework was implemented using Python and rigorously evaluated through experimentation. A comprehensive performance analysis compared the proposed Adaptive Learning Model (ALM) against conventional cryptographic techniques, specifically RSA and AES algorithms. Multiple performance metrics were analysed, and the outcomes demonstrated that the proposed method significantly improves security, scalability, and processing time.
DOI: 10.14419/9f4z3q54
Authors: Thupakula Bhaskar, Hema N, R. Rajitha Jasmine, Pearlin, Uma Patil, Madhava Rao Chunduru, P. Saravanan, Venkatesh Kanna T, R. G. Vidhya
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410209392