Research on Data Privacy Protection Strategies Based on Artificial Intelligence
- DOI
- 10.2991/978-94-6463-264-4_41How to use a DOI?
- Keywords
- data privacy; WOS; artificial intelligence
- ABSTRACT
With the rapid development of big data and artificial intelligence, the importance and urgency of data privacy protection issues have become increasingly prominent, making it a hot research area worldwide. However, the future research directions and hot topics in this field are not yet clear. To this end, this article uses the Web of Science core collection as the data source and uses bibliometrics to visually analyze 1395 related literature on artificial intelligence and data privacy protection, including quantitative analysis of articles, co-citation analysis, and keyword co-occurrence analysis. The results show that although China started relatively late in this field, it has developed rapidly and has become the country with the highest number of publications. The latest research hotspots in the field of data privacy protection focus on blockchain, edge computing and federated learning.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jun Yang AU - Qiukai Ye AU - Jiujiang Han AU - Ming Xian PY - 2023 DA - 2023/09/28 TI - Research on Data Privacy Protection Strategies Based on Artificial Intelligence BT - Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023) PB - Atlantis Press SP - 371 EP - 379 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-264-4_41 DO - 10.2991/978-94-6463-264-4_41 ID - Yang2023 ER -