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Literature Survey on An Efficient Decentralized Identity Management System Based on Range Proof for Social Networks

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Literature Survey on An Efficient Decentralized Identity Management System Based on Range Proof for Social Networks
 
Identifier https://doi.org/10.7910/DVN/ZVNS73
 
Creator Shali Sara Abraham
Demy Devassy
Aiswarya Menon
 
Publisher Harvard Dataverse
 
Description The advent of social networks has revolutionized the way individuals interact and share information. However, concerns related
to privacy, security, and centralized control of user data has become increasingly prominent. In this context, decentralized identity
management systems have emerged as a promising solution to address these challenges. This literature survey paper explores the current
state of research on decentralized identity management systems, with a specific focus on those leveraging range proof techniques for
enhanced efficiency. This paper presents a comprehensive survey of decentralized identity management systems tailored for social
networks, focusing on the integration of range proof techniques to enhance efficiency. With the rising concerns surrounding centralized
control, privacy, and security in social networks, decentralized identity management systems have emerged as a promising alternative.
Range proof techniques play a pivotal role in ensuring data validity without compromising sensitive information. The survey explores
existing decentralized identity systems, scrutinizes their features and limitations, and delves into research integrating range proof
methodologies. Evaluation metrics encompass security, privacy, and efficiency gains, providing a holistic assessment. The paper concludes
by outlining future directions, including scalability, interoperability, and strategies for increased user adoption, thereby contributing to
the evolution of secure and user-centric decentralized identity solutions for social networks.
 
Subject Computer and Information Science
 
Date 2024-01-12