机器学习安全推理研究综述OA

[Objective]This paper analyzes existing research on secure machine learning inference and proposes future research directions.[Methods]Using the security assumptions of different schemes as a basis for classification,this study conducts analysis and comparison of secure inference techniques that utilize various technological combinations for application in differ-ent machine learning contexts.[Results]While current schemes facilitate secure machine learning inference,they exhibit limitations in computational efficiency,security,scalability,and practical applicability.[Limitations]Due to limited data availability,experiments and comparisons of the analyzed schemes under the same benchmark were not conducted.[Con-clusions]Designing secure machine learning inference schemes based on application scenari-os,ensuring security while improving usability and reducing costs,will be a sustained devel-opment direction in this field.