Privacy preserving computing has provided a new model for the circulation and value release of data elements. However, in the face of the blossoming of products, users not only consider the basic functions, performance and security of the product, but also have concerns about whether they can continue data cooperation with organizations that use different products.The cross-platform interconnection of privacy preserving computing has become a key issue affecting the application and promotion of the technology. This paper discusses this issue from the aspects of demand generation, conceptual connotation, practical difficulties, implementation paths, exploration progress and future promotion ideas.
The performance of privacy preserving computing products is one of the main constraints that hinder the large-scale adoption of privacy preserving computing. This paper first introduces the challenges of standardizing the performance of privacy preserving computing products, including an introduction to the main technologies in privacy preserving computing from the perspective of performance and security, as well as the mutual constraints of security, performance and accuracy of privacy preserving computing technologies and the current situation of the lack of uniform performance testing standards. This is followed by a detailed description of the evaluation dimensions of privacy preserving computing products, and concludes with a discussion of the current limitations and future outlook.
Due to security needs and regulatory requirements, the data exchange between entities is about to enter the ciphertext-exchange era. In order to satisfy the needs of data services related to the nation’s livelihood in various industries, the encrypted computing technology must meet the requirements as an infrastructure in terms of security, performance, reliability, applicability, and cost. In this paper, analyze the current status of key technologies required in the ciphertext-exchange era and find that they all have inherently insurmountable drawbacks. This paper proposes a new way of privacy preserving computing: Trusted-environment-based privacy preserving computing, which obtains more robust and balanced integrated properties by combining cryptographic and trusted computing techniques. Then, introduce two typical techniques-controlled anonymization and trusted-environment-based cryptographic computing.
In recent years, both domestic and foreign policies and markets have vigorously promoted the exploration and practice of data flow and transaction, to develop the digital economy. However, due to the core issues such as defining data ownership, effectively controlling the scope of data use, the previous data transaction form has not brought about the prosperity and development of large-scale data flow and the data capitalization market. Through the in-depth analysis of the current situation of data transaction flow and the existing problems, this paper follows the requirements of data security and controllability in the data capitalization flow, which are emphasized in the “Overall Plan for the Comprehensive Reform of Capitalization Market-based Allocation”. Solutions based on privacy-preserving computation is proposed, together with the suggestions for creating a new canonical form for the data capitalization market.
This paper presents a novel vertical federated logistic regression algorithm with provable security guarantees of both model training and inference under the semi-honest security model. The proposed algorithm is privacy-preserving, lossless, and efficient. Firstly, by combining the homomorphic encryption and secret sharing mechanisms, data protection is provably ensured, including the protection of both features and labels. Secondly, the algorithm is lossless since it does not require any approximations for the non-linear functions.
Private preserving computing technology is a method to process data without knowing other participants’ original data. And private preserving computing technology ensures the “availability and invisibility” of data, which has become the technical solution for secure data circulation and has been applied in data-intensive industries. This paper introduces the typical applications of privacy preserving computing in finance, medical, government affairs and some innovative scenarios. Then, we summarize the corresponding application paradigm of these scenarios. In conclusion, we discuss the problems of privacy preserving computing application and analyze its future development trend.
It is essential of data integration between cross institutions and cross industries to promote the better development of Inclusive Finance business. Privacy preserving computing technology has significant advantages to enable the secure computation of the data without revealing the content of the data. It is widely used in the financial industry, especially in inclusive finance. This article introduces the function and significance of multi-source data integration for the development of inclusive finance, as well as the main practices of privacy preserving computing technology. Also, it specifies current technology challenges.
The trend of medical informatization has further enriched the dimension and scale of biomedical data. However, due to the concerns of compliance, privacy-protection and data owner’s benefits, these data are usually stored in different institutions. Therefore, the intrinsic data value within each institution cannot be fully released due to the data isolation. Driven by these factors, privacy preserving computating, which is considered to be one of the most optimal technical solutions, has been rapidly developed and widely applied in many different areas. In this paper, we will introduce privacy preserving computating in Biomedical Areas from the perspective of technology and practical applications.
As the global economy expands through digital transformation at a high pace, the integrated circuit (IC) industry is confronted with tremendous opportunities and challenges, inspired by a new round of development revolutions. Based on the global industrial data shown in annual reports “State of the U.S. Semiconductor Industry”, this paper investigated the current global industrial patterns of the IC industry and analyzed the development paradigm thoroughly from the aspects of evolution, migration and reconstruction. Moreover, it is propitious for a country to seize the latest evolving trends, deepen the understanding of developing rules and improve the policy system, so as to promote overall competitive advantages on the IC industry.
As the growing of memory wall problem and emerging memory applications, the emerging memories are gradually approaching to the commercial application. International giants such as Intel, Samsung, and TSMC have joined in the industrialization of related technologies. Emerging memory technologies mainly include phase-change memory, magnetic-change memory and resistive-change memory. Phase-change memory is ideal for large-capacity stand-alone storage applications, magnetic-change storage is better for small-capacity, high-speed, low-power embedded applications, and resistive storage is likely to play a role in future applications, such as artificial intelligence and process in memory.
As data becomes a new factor of production, the demand for data circulation is growing. However, the sensitive information faces the risk of leakage during the circulation process. Privacy-preserving computing can promote the release of data value while satisfying privacy-preserving constraints. Oblivious keyword search (OKS) is one of the basic tasks of privacy-preserving computing, and it is very important for the application of privacy-preserving computing. In this paper, we first introduce the task definition of OKS and the related tasks. Then, we introduce in detail the typical technical routes of OKS. Finally, we analyze and discuss the technical challenges and future research directions of current OKS technology.
C-RAN architecture is the main way for 5G front-haul, which faces new requirements and challenges compared with D-RAN. Based on the construction of 5G front-haul C-RAN networking, this paper studies the key technologies of 5G front-haul, including WDM technologies and system architectures. The application scenarios of passive and semi-active architectures are analyzed. The progress of standardization and industry are summarized, and the 5G front-haul C-RAN networking is prospected and analyzed.