Title data
Duda, Sebastian ; Geyer, Dorian ; Guggenberger, Tobias ; Principato, Marc ; Protschky, Dominik:
A Systematic Literature Review on How to Improve the Privacy of Artificial Intelligence Using Blockchain.
In:
Proceedings of the Pacific Asia Conference on Information Systems (PACIS). -
Taipei/Sidney, Taiwan/Australia
,
2022
Related URLs
Project information
Project title: |
Project's official title Project's id Projektgruppe WI BLockchain-Labor No information Projektgruppe WI Künstliche Intelligenz No information |
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Abstract in another language
Artificial Intelligence applications rely on large amounts of data. These Artificial Intelligence applications often also process personal data, leading to privacy problems. At the same time, the regulations regarding the use of data and privacy are getting stricter (e.g., the Personal Information Protection Law). Therefore, in this work, we investigate how Blockchain could help to improve the privacy of Artificial Intelligence applications. We conducted a systematic literature review to analyze existing approaches in the literature and abstracted them into categories. We identify federated learning in combination with Trained Model Sharing as the most popular approach. Additionally, we find that cryptographic methods usually complement most approaches, and that central collection and storage of raw data is not an option for any approach. Our work may serve as a foundation for developing a modular kit for privacy-preserving Blockchain-AI-systems.
Further data
Item Type: | Article in a book |
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Refereed: | Yes |
Additional notes: | Paper Number 1616 |
Keywords: | Blockchain; Artificial Intelligence; Technology Convergence; Privacy |
Institutions of the University: | Faculties > Faculty of Law, Business and Economics > Department of Business Administration Research Institutions Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management Faculties Faculties > Faculty of Law, Business and Economics |
Result of work at the UBT: | Yes |
DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics |
Date Deposited: | 04 Jul 2022 08:49 |
Last Modified: | 12 Jul 2022 06:41 |
URI: | https://eref.uni-bayreuth.de/id/eprint/70371 |