As the value brought about by data utilization is attracting attention, the global big data market has been making growth at an annual rate of more than 10 and is estimated to reach a scale of about 20 trillion yen by 2020.In line with this trend, development of laws for promoting proper data distribution and utilization has progressed on a global basis, and technologies to meet the requirements of those laws are beginning to come into practical use.However, there are also anxieties expressed arising from the inability to make decisions regarding risks in personal data distribution; individuals may agree to data distribution without realizing how high the risk is, or business owners may cause privacy issues by distributing personal data with low anonymity, possibly resulting in major losses such as compensation for damages.To deal with these issues, Fujitsu Laboratories has developed a technology to quantify privacy risks from personal data disclosures in terms of monetary value.We have also developed a model for calculating the identifiability (how low anonymity is) of data after anonymization, which was insufficient in the past, and confirmed that these are applicable to real data.Furthermore, we have developed a high-speed identifiability calculation technology that allows for the calculation of data sets on a scale of 1 million people in about an hour with a general performance PC, confirming adequate practicability.This paper describes the technology that allows for risk evaluations regarding personal data and the concept of realizing a society that can better extract the value of data by utilizing this technology.
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