Privacy Computing: Concept, Computing Framework, and Future Development Trends

• Main Authors: Fenghua Li, Hui Li, Ben Niu, Jinjun Chen
• Format: Article
• Language: English
• Published: Elsevier 2019-12-01
• Series: Engineering
• Online Access: http://www.sciencedirect.com/science/article/pii/S2095809919308240

With the rapid development of information technology and the continuous evolution of personalized services, huge amounts of data are accumulated by large internet companies in the process of serving users. Moreover, dynamic data interactions increase the intentional/unintentional persistence of private information in different information systems. However, problems such as the cask principle of preserving private information among different information systems and the difficulty of tracing the source of privacy violations are becoming increasingly serious. Therefore, existing privacy-preserving schemes cannot provide systematic privacy preservation. In this paper, we examine the links of the information life-cycle, such as information collection, storage, processing, distribution, and destruction. We then propose a theory of privacy computing and a key technology system that includes a privacy computing framework, a formal definition of privacy computing, four principles that should be followed in privacy computing, algorithm design criteria, evaluation of the privacy-preserving effect, and a privacy computing language. Finally, we employ four application scenarios to describe the universal application of privacy computing, and discuss the prospect of future research trends. This work is expected to guide theoretical research on user privacy preservation within open environments. Keywords: Privacy computing, Private information description, Privacy metric, Evaluation of the privacy-preserving effect, Privacy computing language