Current Result Document :
| 한글제목(Korean Title) |
A Study on Protecting Privacy of Machine Learning Models |
| 영문제목(English Title) |
A Study on Protecting Privacy of Machine Learning Models |
| 저자(Author) |
Younghan Lee
Woorim Han
Yungi Cho
Hyunjun Kim
Yunheung Paek
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| 원문수록처(Citation) |
VOL 28 NO. 02 PP. 0061 ~ 0063 (2021. 11) |
한글내용
(Korean Abstract) |
Machine learning model gained the popularity in recent years as multi-national companies have incorporated machine learning in their services. Such service is called machine learning as a service (MLaSS). Such services are provided to users based on charge-per-query which triggers the motivations for adversaries to steal the trained victim model to reduce the cost of using the service. Therefore, it is important for companies that provide MLaSS to protect their intellectual property (IP) against adversaries. It has been arms race between the attack and defence in a context of the privacy of machine learning models. In this paper, we provide a comprehensive study of recent development in protecting privacy of machine learning models.
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영문내용
(English Abstract) |
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| 키워드(Keyword) |
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| 파일첨부 |
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