Author: Zen and the Art of Computer Programming
1 Introduction
Summary
With the rapid development of science and technology, artificial intelligence technology has become one of the important forces in today's era, and is gradually being implemented in both the medical and health fields and the social and economic fields. However, deep learning, one of the key technologies of artificial intelligence, also brings new security and privacy issues. This article will elaborate on the main privacy and security threats of current artificial intelligence technology in data security and provide corresponding solutions. It is hoped that through a detailed analysis of data security, model security, model training process and other aspects of AI technology, readers can better understand and grasp the challenges of AI technology in data security and privacy protection, and formulate action plans to improve Contribute to the application level of artificial intelligence technology at home and abroad.
Keywords
AI technology, data security, privacy protection, model security, model training process
About the Author
Zhang Mingmin, a doctoral student, once worked at Tencent; he won the 2019 Computer Vision International Conference Excellence Award. Currently, he is a researcher at the School of Software, Tsinghua University.
2. Background introduction
Artificial Intelligence (AI) refers to the ability of computers to simulate intelligent robots, usually including autonomous learning, reasoning, communication and decision-making. Its application range is wide and diverse, mainly involving intelligent computing, image recognition, language processing, speech synthesis, target recognition, decision analysis and other fields. With the continuous progress and development of artificial intelligence technology, the amount of data generated, data types, processing methods, etc. are becoming more and more complex. How to ensure the security and privacy of data generated by artificial intelligence technology has always been a topic worthy of attention and pursuit.
In the application process of AI technology, data security and privacy security are particularly important. Here are some common scenarios:
Data leakage problem: Due to data transmission or storage on the network, data is stolen, tampered with, leaked, etc. For example, in medical imaging diagnosis, the original images uploaded by the patient may contain the patient's personal information.