R&D on Secure Computation Technology for Privacy Protection

1. Introduction

Innovation in information and communication technology is making it possible to collect and analyze large amounts of diverse data, and there are increasingly high expectations for value creation by using big data. In particular, various efforts have been made recently to enable secondary use of personal data for the development of society and industry. The term personal data is not limited to the data defined by the Personal Information Protection Law, but is used in the broader sense of all information that concerns individuals [1]. Businesses that handle personal data are responsible for giving sufficient consideration to the privacy of the individuals who provide that information and for taking appropriate security management measures. Article 20 of the Personal Information Protection Law, Measures for Security Management, states that “Businesses that handle personal data must prevent the leaking, loss, or damage of that personal data and devise other appropriate measures for managing the security of personal data.” In general, obtaining the consent of the person in respect to the purposes for using personal data is different from taking measures required by the Measures for Security Management. Leakage of personal data after the business obtains consent is an issue of responsibility, and such leakages reduce the public’s trust.

The problem, then, is what security management measures are necessary and appropriate for the secondary use of personal data. Consider, for example, the situation in which individuals and businesses provide personal data to cloud providers, the cloud providers process the personal data for provision to secondary users, and the secondary users use the results of that processing (Fig. 1). In this case, the processing results consist of analysis results or anonymized personal data. The cloud provider is required to take security management measures for the obtained personal data and also for the processing results provided to the secondary user. In particular, the suppliers of the personal data cannot directly manage or control the personal data supplied to the cloud provider, and therefore, they probably worry about the possible leakage or unintended use of that data. This concern about security is cited as the most important factor in decisions to refrain from using cloud services. The concept known as secure computation has been attracting attention as a technological solution for security management that solves that problem by preventing the leakage or misuse of personal data and by maintaining privacy. In the remainder of this article, we present an overview of technology related to secure computation and describe the work being done at the NTT Secure Platform Laboratories.

Fig. 1. Example process of secondary use of personal data.

2. Secure computation

Secure computation technology allows statistical processing and other kinds of data processing to be performed on data that remains in a secure form. One security measure used when information is entrusted to the cloud is data encryption. When the data processing is also done in the cloud, the processing is not usually performed with the data in the encrypted state, so the data must be decrypted in the cloud, which creates a risk of data leakage.

Secure computation is a technology that reduces that risk. A secure computation system is illustrated schematically in Fig. 2. First, the possessor of the data to be used in statistical processing or another form of processing sends the anonymized data to a secure computation system. Next, the analyzing party that wants to do the processing sends a request for analysis to the secure computation system. The secure computation system then performs the processing on the data that is still in the anonymized form and sends only the results to the party that requested the analysis. The special feature of secure computation is that the data is never decrypted, and the requesting party never receives anything other than the analysis results.

Fig. 2. Basic system model of secure computation.

The secure computation technology that is currently under development is implemented by the interworking of multiple computers (secure computation servers) that communicate with each other. The input data is first anonymized with a secret-sharing algorithm and then distributed among the secure computation servers. The secure computation servers perform the processing while exchanging the anonymized data among themselves. The simplest example of secure computation processing is illustrated in Fig. 3.

Fig. 3. Simple example of secure computation processing.

In Fig. 3, person A (Alice) and person B (Bob) have test scores. We want to obtain the average score for these two people without anyone learning what the individual test scores are. To obtain that result, the two test scores are first processed by implementing secret distribution. Specifically, each score is split into three numbers whose sums are the original scores. Those three distributed numbers are sent to secure computation servers, which then add up the received data. Finally, the resulting numbers are summed, and the sum is divided by the number of persons (two in this case) to obtain the ultimate result, which is the average test score for the two people (77 in this example). The numerical values used within the secure computation servers are unrelated to the original test scores, so the privacy of person A and person B is preserved.

The method depicted in Fig. 3 can only be used to obtain an average value. In 1982, however, A. C. Yao proposed a method that enables secure computation for any type of processing [2], although it was impractical for processing very large amounts of data. Research to improve efficiency has continued since that time, however. Research on secure computation began over ten years ago at the NTT Secure Platform Laboratories, and we achieved the world’s fastest processing in 2005 [3]. Good compatibility between secure computation and statistical processing has also been discovered in recent years, and experiments that verify practical performance have been conducted [4].

3. Overview of the Trust-SC secure computation platform

Trust-SC is the first on-line statistical analysis system that was developed applying secure computation technology for commercial use. NTT Secure Platform Laboratories keeps striving to be a world leader in research on secure computation technology, and this on-line service makes it possible to analyze data and obtain results of statistical analysis without reconstructing any master data.

An overview of the Trust-SC platform is presented in Fig. 4. The main features are explained in the following subsections.

Fig. 4. Trust-SC secure computation platform.

4. Future development

Research on secure computation was previously only theoretical, but practical research has suddenly accelerated with the demand for security management in the secondary use of personal data, and practical goals have been established. The NTT Secure Platform Laboratories has developed the world’s first commercial-level secure computation system and confirmed the ability of the system to carry out data analysis processing on a data scale of 100,000 items in a practical amount of time.

Our future tasks include developing the system so that it is capable of handling data on a larger scale for use in big data applications, and adopting a social scientific approach to research that supports relevant laws in order to give users a greater sense of security.

References

	Koji Chida Senior Research Engineer, Information Security Project, NTT Secure Platform Laboratories. He received the B.S. and M.S. from Waseda University, Tokyo, in 1998 and 2000, respectively. Since 2000, he has been engaged in research on cryptography and privacy enhancing technologies at NTT. He received the Dr. Eng. degree from Waseda University in 2006. He is a member of the Information Processing Society of Japan (IPSJ). He was awarded the IPSJ Best Paper Award in 2012.
	Dai Ikarashi Researcher, Information Security Project, NTT Secure Platform Laboratories. He received the B.S. and M.S. from The University of Tokyo in 2005 and 2008, respectively. Since 2008, he has been engaged in research on cryptography and information security at NTT. He is a member of the IPSJ.
	Teruko Miyata Senior Research Engineer, Security Management & Operations Project, NTT Secure Platform Laboratories. She received the B.S. and M.S. in mathematical science from Ochanomizu University, Tokyo, in 1991 and 1993, respectively. She joined NTT laboratories in 1993. Her current fields of interests are protection technology of privacy and identity management.
	Hiroyoshi Takiguchi Research Engineer, Security Management & Operations Project, NTT Secure Platform Laboratories. He received the B.S. and M.S. in human-environment studies from Kyushu University, Fukuoka, in 2000 and 2002, respectively. He joined NTT laboratories in 2003. His current fields of interests are protection technology of privacy and identity management.
	Naoto Kiribuchi Security Management & Operation Project, NTT Secure Platform Laboratories. He received the B.E. and M.E. in informatics from the University of Electro-Communications, Tokyo, in 2010 and 2012, respectively. He joined NTT laboratories in 2012. His current fields of interests are cryptography and information security.