Blockchain-Based Identity Management: Enhancing Privacy and Security in Digital Identity System

Privacy and security are major concerns when it comes to digital identities, particularly in centralized systems where data can be easily hacked or where people engage in identity fraud. These issues can be addressed using blockchain technology since it allows for the creation of a decentralized digital identity that is both secure and tamper-proof. This study employs Kaggle dataset to document the transactions and the devices involved to make the distinctions on how blockchain can boost privacy and security. Predominantly, various machine learning algorithms are used to analyze blockchain applications, and the results emphasize the fact blockchain systems greatly enhance transaction viability and diminish fraudulent actions. Therefore, the study argues that blockchain-based identity management systems offset the shortcomings of the centralized model by enhancing data ownership and combating fraud. Subsequent analysis expanded on the discussion of elaborating the scalability, interoperability, and application of algorithms to blockchains as well as how it can fundamentally change the way that certain industries, particularly identity management, would work with consumers at the center of reliable and secure blockchain solutions.

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Published
2024-09-18
DOI
https://doi.org/10.1109/ic3i61595.2024.10829044
Citations
1
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.78
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Blockchain-Based Identity Management: Enhancing Privacy and Security in Digital Identity System

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article

Blockchain-Based Identity Management: Enhancing Privacy and Security in Digital Identity System

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article en
1 citations

Abstract

Privacy and security are major concerns when it comes to digital identities, particularly in centralized systems where data can be easily hacked or where people engage in identity fraud. These issues can be addressed using blockchain technology since it allows for the creation of a decentralized digital identity that is both secure and tamper-proof. This study employs Kaggle dataset to document the transactions and the devices involved to make the distinctions on how blockchain can boost privacy and security. Predominantly, various machine learning algorithms are used to analyze blockchain applications, and the results emphasize the fact blockchain systems greatly enhance transaction viability and diminish fraudulent actions. Therefore, the study argues that blockchain-based identity management systems offset the shortcomings of the centralized model by enhancing data ownership and combating fraud. Subsequent analysis expanded on the discussion of elaborating the scalability, interoperability, and application of algorithms to blockchains as well as how it can fundamentally change the way that certain industries, particularly identity management, would work with consumers at the center of reliable and secure blockchain solutions.

Mangalmay Institute of Management and Technology, Saveetha University (IN), Vellore Institute of Technology University (IN)
Reduced inequalities
Openalex Percentile: Top 18%
Blockchain Technology Applications and Security
0.78
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