| Data Infrastructure for Risk Analysis | |
| Mathematical Risk Analysis | |
| Environmental Risk Analysis | |
| Risk Analysis for Resource Management | |
| Statistical Seismology | |
| Spatio-Temporal Statistical Modeling and Applications |
● Statistical disclosure control
● Security management for receipt data
● Quality management for statistics and microdata
● System science for risk information dissemination
■ Facilitate secondary use of official microdata
Facility on-site at the Institute of Statistical MathematicsWe have been supporting government services to enable the secondary use of official microdata, such as the publication of anonymized statistical data under a 2010 partnership agreement with the National Statistics Center and the Research Organization of Information and Systems (ROIS). We also launched an on-site remote microdata access service in 2017 where researchers can access microdata, including that of nine other Asian countries, in a physically secure environment.
■ Building Fusion Technologies of Advanced Cryptography and Statistical Disclosure Control (SDC), and Providing Practical Guidelines for Privacy Protection
Seamless Integration of Advanced Cryptography and SDC Techniques
Today, the use of microdata on individuals and organizations collected by companies and government agencies is drawing growing attention. Yet even when only summary statistics or analysis results are shared, there is still a risk that confidential information from the original data may be revealed. To address this, Statistical Disclosure Control (SDC) techniques are applied to ensure safe data release.
Our project brings together advanced cryptographic technologies—which make it possible to perform calculations on encrypted data—with SDC methods.
By systematizing this fusion, we aim to protect data throughout its entire lifecycle. At the same time,
we provide practical guidelines that help society put strong privacy protection into practice while enabling secure and trustworthy data sharing.
Project SDC4Society（https://www.sdc4society.org/en/）
■ Establish a conceptual basis for risk science
Procedure for establishing quantitative risk science
We aim to define basic principles in mathematical statistics and risk information theory that are applicable to various research fields in the risk sciences such as quantitative risk science and risk information management, by collaborating with other institutes in the risk research network. We identify key concepts in risk science, such as individual, unified, potential, and mathematical risks, and define the corresponding research disciplines to cover the revelation, discovery, structural analysis, and crisis management of risks.