Titlebar

Export bibliographic data
Literature by the same author
plus on the publication server
plus at Google Scholar

 

A Systematic Literature Review on How to Improve the Privacy of Artificial Intelligence Using Blockchain

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

Project information

Project title:
Project's official titleProject's id
Projektgruppe WI BLockchain-LaborNo information
Projektgruppe WI Künstliche IntelligenzNo information

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
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