Multilateral Personal Portfolio Authentication System Based on Hyperledger Fabric
- Authors
- Jeong, Junho; Kim, Donghyo; Ihm, Sun-Young; Lee, Yangsun; Son, Yunsik
- Issue Date
- Feb-2021
- Publisher
- ASSOC COMPUTING MACHINERY
- Keywords
- Blockchain; authentication; e-business model; personal portfolio; hyperledger fabric
- Citation
- ACM TRANSACTIONS ON INTERNET TECHNOLOGY, v.21, no.1
- Indexed
- SCIE
SCOPUS
- Journal Title
- ACM TRANSACTIONS ON INTERNET TECHNOLOGY
- Volume
- 21
- Number
- 1
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/5401
- DOI
- 10.1145/3423554
- ISSN
- 1533-5399
1557-6051
- Abstract
- Korean education-related evaluation agencies utilize a centralized system that directly manages learner data. This leaves the intellectual property of the organizations and the personal information of the students vulnerable to leakage should the central server be attacked. In this study, the researchers propose a multilateral personal portfolio authentication system that guarantees the reliability, integrity, and transparency of the data such as learner's schooling history. The system uses the features of blockchain in a distributed network wherein a learner submits schooling data to a peer in the network. The data is then verified through an agreement among the peers and recorded in a chronologically encrypted ledger. The proposed system is implemented based on Hyperledger Fabric and the analysis thereof conducted by evaluating its processing speed, capacity, and security. The analysis indicates that the system is able to successfully intercept the transactions of unvalidated users, thereby preventing the recording of incorrect data by an unauthorized user. Furthermore, it provides a record of previously made changes to a learner's profile, thus improving the integrity and reliability of the data. This system provides a platform to share learner information safely and promptly among schools, certification authorities, and higher learning institutions.
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Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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