• Informatization Policy
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• v.27 no.3
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• pp.82-111
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• 2020

Recently, increasing use of big data have caused regulation factors of personal information and combination of pseudonymized information to emerge as key policy measures. Therefore, this study empirically analyzed the mediating effect and moderating effect of pseudonymized information combination as the third variable in the relationship between regulation factors of personal information and big data utilization. The analysis showed the following results: First, among personal information regulation factors, definition regulation, consent regulation, supervisory authority regulation, and punishment intensity regulation showed a positive(+) relationship with the big data utilization, while among pseudonymized information combination factors, non-identification of combination, standardization of combined pseudonymized information, and responsibility of combination were also found to be in a positive relationship with the use of big data. Second, among the factors of pseudonymized information combination, non-identification of combination, standardization of combined pseudonymized information, and responsibility of combination showed a positive(+) mediating effect in relation to regulation factors of personal information and big data utilization. Third, in the relationship between personal information regulation factors and big data utilization, the moderating effect hypothesis that each combination institution type of pseudonymized information (free-type, intermediary-type, and designated-type) would play a different role as a moderator was rejected. Based on the results of the empirical research, policy alternatives of 'Good Regulation' were proposed, which would maintain balance between protection of personal information and big data utilization.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.427-430
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• 2024

교통체계서비스는 안전한 교통 환경을 구축하는 것을 목표로 하여 차량, 도로, 기반 시설의 정보를 수집 및 처리하여 안전 교통정보를 제공한다. 교통체계서비스가 수집하는 차량 운행정보는 교통 안전 정보 외에도 다른 분야에서도 활용될 수 있으며 특히 다른 데이터와 결합하는 것으로 다양한 결과를 도출할 수 있어 연구, 통계 작성 등에 필요한 자료이다. 그러나 차량의 운행정보는 운전자의 개인정보를 포함하고 있어 운행정보 활용 시 가명화 및 가명결합이 필수적이다. 본 논문에서는 가명화된 운행정보를 가명결합하는데 발생하는 문제점을 설명하고 이러한 문제를 해결한 가명결합 방안을 연구하였다. 그 결과 교통체계서비스가 수집한 운행정보를 다른 기관의 데이터와 결합하여 활용할 수 있게 하여 개인정보를 보호하면서 데이터의 유용성을 활용하는데 기여할 것으로 예상한다.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.17-22
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• 2021

With the application of the Data 3 method, the scope of the use of pseudonym information has expanded. In the case of pseudonym information, a specific individual can be identified by linking and combining with various data, and personal information may be leaked due to incorrect use of the pseudonym information. In this paper, we propose the scope of use of data is subdivided and a differentiated pseudonym information processing method according to the scope. For the study, the formula was modified by using zero-knowledge proof among the pseudonym information processing methods, and when the proposed formula was applied, it was confirmed that the performance improved by an average of 10% in terms of verification time compared to the case of applying the formula of the existing zero-knowledge proof.

• Review of KIISC
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• v.32 no.4
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• pp.77-84
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• 2022

2020년 8월 5일 통합 개인정보보호법 [3]이 본격적으로 시행되면서 데이터의 보호와 활용을 동시에 만족할 수 있는 가명처리 개념이 도입되었다. 여러 개인정보처리자로 수집된 가명정보를 결합하기 위한 결합 관리기관이 지정되고 있다. 개인정보보호 국제표준은 관행이나 기술을 국제표준으로 개발하여 상호 연동이 가능한 서비스를 제공할 수 있을 뿐만 아니라 제품이나 서비스의 경쟁력을 강화하는데 활용할 수 있다. 개인정보보호 국제표준화를 주도적으로 추진하고 있는 대표적인 국제표준화 그룹은 국제표준화위원회/전기위원회 합동위원회 1/서브위원회 27/작업그룹 5 (ISO/IEC JTC 1/SC 27/WG 5)를 들 수 있다. 이 그룹의 의장님 독일 쾨테대학 Kai Rannenberg 교수가 맡고 있다. 여기서는 2020년 4월 전자회의 이후에는 개인정보보호 분야 3건의 국제표준을 채택하였다. 차기 회의는 2022년 9월 룩셈부르그에서 펜데믹 이후 최초로 대면과 비대면으로 개최될 예정이다. 본 고에서는 이 그룹에서 2020년 4월 이후 추진되고 있는 개인정보보호 관련 국제표준화 동향을 제시하고자 한다. 또한 지난 4월 SC27 WG5 전자 회의에서 논의된 개인정보보호 관련 주요 표준화 이슈와 대응 방안을 제시한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.48-66
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• 2024

According to the three amended Laws of the Data Economy and the Data Industry Act of Korea, systems for pseudonymous data integration and Data Safe Zones have been operated separately by selected agencies, eventually causing a burden of use in SMEs, startups, and general users because of complicated and ineffective procedures. An over-stringent pseudonymization policy to prevent data breaches has also compromised data quality. Such trials should be improved to ensure the convenience of use and data quality. This paper proposes a prototype system of the Integrated Data Safe Zone based on redesigned and optimized pseudonymization workflows. Conventional workflows of pseudonymization were redesigned by applying the amended guidelines and selectively revising existing guidelines for business process redesign. The proposed prototype has been shown quantitatively to outperform the conventional one: 6-fold increase in time efficiency, 1.28-fold in cost reduction, and 1.3-fold improvement in data quality.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.915-932
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• 2022

According to the Personal Information Protection Act and Pseudonymization Guidelines, the mapping is processed to the hash value of the combination key generation items including Salt value when different combination applicants wish to combine. Example of combination key generation items may include personal information like name, phone number, date of birth, address, and so on. Also, due to the properties of the hash functions, when different applicants store their items in exactly the same form, the combination can proceed without any problems. However, this method is vulnerable to combination in scenarios such as address changing and renaming, which occur due to different database update times of combination applicants. Therefore, we propose a privacy preserving combination key generation scheme robust to updates of items used to generate combination key even in scenarios such as address changing and renaming, based on the thresholds through probabilistic record linkage, and it can contribute to the development of domestic Big Data and Artificial Intelligence business.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.88-103
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• 2023

With the recent advancement of 4th Industrial Revolution technology, transportation systems are generating large amounts of mobility data related to the individual movement trajectories of vehicles and people. There are many constraints on utilizing mobility data containing personal information. Thus, in South Korea, the processing and generation of pseudonymized information and the analysis and utilization of this information have been managed in a dual manner by applying separate agencies and technologies through the revision of the Data 3 Act and the enactment of the Data Basic Act. However, this dual approach fails to securely support the entire data lifecycle and suffers from inefficiencies in terms of processing time and cost. Therefore, to compensate for the problems of the existing Expert Data Combination System and Data Safety Zone, this study proposes an Integrated Data Safety Zone Framework that integrates and unifies the process of generating, processing, analyzing, and utilizing mobility data. The integrated process for data processing was redesigned, and common requirements and core technologies were derived. The result is an architecture for a next-generation Integrated Data Safety Zone system that can manage and utilize the entire life cycle of mobility data at one stop.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.2
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• pp.253-261
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• 2020

This study examines the technologies and application processes related to the use of pseudonym data of companies after the passage of the Data 3 Act to activate the data economy in earnest, and what companies should prepare to use pseudonym data and what will happen in the process It was intended to contribute to the elimination of uncertainty. In the future, companies will need to extend the information security management system from the perspective of the existing IT system to manage and control data privacy protection and management from a third party provisioning perspective. In addition, proper pseudonym data use control should be implemented even in the data use environment utilized by internal users. The economic effect of market change and heterogeneous data combination due to the use of pseudonymized data will be very large, and standards for appropriate non-identification measures and risk assessment criteria for data utilization and transaction activation should be prepared in a short time.

• The Journal of Bigdata
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• v.7 no.2
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• pp.75-90
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• 2022

Recently, complex and sophisticated analysis of transportation is required due to changes in the socioeconomic environment and the development of bigdata technology. Especially, the revision of 3 laws including PERSONAL INFORMATION PROTECTION ACT makes it possible to combine various types of mobility data. But strengthen personal information protection makes inefficiency in utilizing mobility bigdata. In this paper, we proposed the "Virtual fusion methdology via mobility bigdata" which is a methodology for indirect data fusion for various mobility bigdata such as mobile data and transportation card data, in order to resolve legal restrictions and enable various transportation analysis. And we also analyzed regional bus passenger in Seoul capital area and Cheongju city with aforementioned methodology for verification. This methdology could analyze behavioral pattern of passenger with the MCGM(Mobility Comprehensive Genetic Map), graph with position and time, making with mobile data. Consquently, using MCGM, which is a result for indirect data fusion, makes it possible to analyze various transportation problems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.2
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• pp.287-304
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• 2020

There have been a number of legal & policy studies on the affecting factors of big data utilization, but empirical research on the composition factors of personal information regulation or data combination, which acts as a constraint, has been hardly done due to the lack of relevant statistics. Therefore, this study empirically explores the priority of personal information regulation factors and data combination factors that influence big data utilization through Delphi Analysis. As a result of Delphi analysis, personal information regulation factors include in order of the introduction of pseudonymous information, evidence clarity of personal information de-identification, clarity of data combination regulation, clarity of personal information definition, ease of personal information consent, integration of personal information supervisory authority, consistency among personal information protection acts, adequacy punishment intensity in case of violation of law, and proper penalty level when comparing EU GDPR. Next, data combination factors were examined in order of de-identification of data combination, standardization of combined data, responsibility of data combination, type of data combination institute, data combination experience, and technical value of data combination. These findings provide implications for which policy tasks should be prioritized when designing personal information regulations and data combination policies to utilize big data.