边缘计算下差分隐私的应用研究综述

Survey of Application of Differential Privacy in Edge Computing

为了解决传统云计算模式的延迟和带宽限制,应对物联网和大数据时代的需求,边缘计算开始崭露头角并逐渐受到广泛关注。在边缘计算环境下,用户数据的隐私问题成为了一个重要的研究热点。差分隐私技术有着坚实的数学基础,它作为一种有效的隐私保护算法,已经被广泛应用于边缘计算中,两者的结合有效缓解了隐私保护低和计算成本高的问题。首先介绍了互联网发展带来的问题,其次介绍了边缘计算的基本概念、特点和组成部分,并概括了与传统云计算相比的优势,然后对差分隐私的基本概念和原理进行了概括,进而详细阐述了差分隐私的3种扰动方式和常用的实现机制,最后对边缘计算下差分隐私的应用研究进行了综述,并指出了未来的研究方向。总之,将差分隐私技术应用于边缘计算场景对隐私保护和数据分享都是一种有效保护手段。

In order to address the latency and bandwidth limitations of the traditional cloud computing model and to cope with the demands of the Internet of Things and the big data era,edge computing is making its appearance and gaining widespread attention.In the edge computing environment,the privacy of user data has become an important research hotspot.The combination of differential privacy techniques,which have a solid mathematical foundation,has been widely used in edge computing as an effective privacy-preserving algorithm to improve the problem of low privacy protection and high computational cost.The problems brought about by the development of the Internet are firstly introduced,followed by the basic concepts,features and components of edge computing,and the advantages compared with traditional cloud computing are outlined.The basic concepts and principles of differential privacy are again outlined,followed by a detailed description of the three perturbation methods and common implementation mechanisms of differential privacy,and finally the research on the application of differential privacy under edge computing is reviewed.Finally,the research on the application of differential privacy under edge computing is reviewed and future research directions are pointed out.In conclusion,the application of differential privacy techniques to edge computing scenarios is an effective means to protect privacy and data sharing.