• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.101-108
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• 2017

The study proposed a system that filters the data that is entered when analyzing big data such as SNS and BLOG. Personal information includes impersonal personal information, but there is also personal information that distinguishes it from personal information, such as religious institution, personal feelings, thoughts, or beliefs. Define these personally identifiable information as sensitive information. In order to prevent this, Article 23 of the Privacy Act has clauses on the collection and utilization of the information. The proposed system structure is divided into two stages, including Big Data Processing Processes and Sensitive Information Filtering Processes, and Big Data processing is analyzed and applied in Big Data collection in four stages. Big Data Processing Processes include data collection and storage, vocabulary analysis and parsing and semantics. Sensitive Information Filtering Processes includes sensitive information questionnaires, establishing sensitive information DB, qualifying information, filtering sensitive information, and reliability analysis. As a result, the number of Big Data performed in the experiment was carried out at 84.13%, until 7553 of 8978 was produced to create the Ontology Generation. There is considerable significan ce to the point that Performing a sensitive information cut phase was carried out by 98%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7C
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• pp.667-673
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• 2007

In order to provide the efficient personalized services, the organizations and the companies collect and manage the personal information. The stored data have some slight differences among each subject. Even though the same attribute information leaks out, the personal privacy violation is different according to personal sensitivity. However, currently the organizations or the companies protect all the information as the same level. This paper reflects the sensitive attribute information of the information subject to each personal policy by the encrypting techniques. And then we propose a policy-based access control mechanism for the personal information which strictly prevents unauthorized information users from illegally accessing the personal information. In the proposed mechanism, the individuals' personal information which is encrypted with different keys is stored into the database. For the access control, information subjects set up their own access control policy for their sensitive personal information. Then it is possible to control the information access by providing the information to the information users according to personal and organizational privacy policy.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.34-41
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• 2020

An era of stabilizing IoT markets and rapid expansion is coming. In an IoT environment, communication environments where objects take the lead in communication can occur depending on the situation, and communication with unspecified IoT environments has increased the need for thorough management of personal sensitive information. Although there are benefits that can be gained by changing environment due to IoT, there are problems where personal sensitive information is transmitted in the name of big data without even knowing it. For the safe management of personal sensitive information transmitted through sensors in IoT environment, the government plans to propose measures to enhance information protection in IoT environment as the use of non-identifiable personal information in IoT environment is expected to be activated in earnest through the amendment of the Data 3 Act and the initial collection method.

• Journal of Information Technology Services
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• v.22 no.6
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• pp.1-15
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• 2023

This study compares and analyzes the legal systems of Korea, the European Union, China, and the United States based on the disclosure principles and processing policies for personal data processing and provides references for seeking improvements in our legal system. Furthermore, this research aims to suggest institutional implications to overcome data transfer limitations in the upcoming digital economy. Findings on a comparative analysis of the relevant legal systems for disclosing privacy policies in four countries showed that Korea's privacy policy is under the eight principles of privacy proposed by the OECD. However, there are limitations in the current situation where personal information is increasingly transferred overseas due to direct international trade e-commerce. On the other hand, the European Union enacted the General Data Protection Regulation (GDPR) in 2016 and emphasized the transfer of personal information under the Privacy Policy. China also showed differences in the inclusion of required items in its privacy policy based on its values and principles regarding transferring personal information and handling sensitive information. The U.S. CPRA amended §1798.135 of the CCPA to add a section on the processing of sensitive information, requiring companies to disclose how they limit the use of sensitive information and limit the use of such data, thereby strengthening the protection of data providers' rights to sensitive information. Thus, we should review our privacy policies to specify detailed standards for the privacy policy items required by data providers in the era of digital economy and digital commerce. In addition, privacy-related organizations and stakeholders should analyze the legal systems and items related to the principles of personal data disclosure and privacy policies in major countries so that personal data providers can be more conveniently and accurately informed about processing their personal information.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.43-49
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• 2019

Today, with the development of the internet of things, wearable devices related to personal health care have become widespread. Various global information and communication technology companies are developing various wearable health devices, which can collect personal health information such as heart rate, steps, and calories, using sensors built into the device. However, since individual health data includes sensitive information, the collection of irrelevant health data can lead to personal privacy issue. Therefore, there is a growing need to develop technology for collecting sensitive health data from wearable health devices, while preserving privacy. In recent years, local differential privacy (LDP), which enables sensitive data collection while preserving privacy, has attracted much attention. In this paper, we develop a technology for collecting vast amount of health data from a smartwatch device, which is one of popular wearable health devices, using local difference privacy. Experiment results with real data show that the proposed method is able to effectively collect sensitive health data from smartwatch users, while preserving privacy.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.103-110
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• 2008

Due to the development of the e-commerce, the shopping mall such as auction collects and manages the personal information of the customers for efficient service. However, because of the leakage of the Personal information in auction, the image of the companies as well as the information subjects is damaged. Even though the organizations and the companies store the personal information as common sentences and protect using role based access control technique, the personal information can be leaked easily in case of getting the authority of the database administrator. And also the role based access control technique is not appropriate for protecting the sensitive information of the information subject. In this paper, we encrypted the sensitive information assigned by the information subject and then stored them into the database. We propose the personal policy based access control technique which controls the access to the information strictly according to the personal policy of the information subject. Through the proposed method we complemented the problems that the role based access control has and also we constructed the database safe from the database administrator. Finally, we get the control authority about the information of the information subject.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.6
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• pp.66-76
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• 2017

In this study, we investigated how to protect personal healthcare information when constructing OMOP (Observational Medical Outcomes Partnership) CDM (Common Data Model). There are two proposed methods; to restrict data corresponding to HIPAA (Health Insurance Portability and Accountability Act) PHI (Protected Health Information) to be extracted to CDM or to disable identification of it. While processing sensitive information is restricted by Korean Personal Information Protection Act and medical law, there is no clear regulation about what is regarded as sensitive information. Therefore, it was difficult to select the sensitive information for protecting personal healthcare information. In order to solve this problem, we defined HIPAA PHI as restriction criterion of Article 23 of the Personal Information Protection Act and maps data corresponding to CDM data. Through this study, we expected that it will contribute to the spread of CDM construction in Korea as providing solutions to the problem of protection of personal healthcare information generated during CDM construction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.47-49
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• 2021

According to the revision of the Data 3 Act in 2020, personal information of medical data can be processed anonymously for statistical purposes, research, and public interest record keeping. However, unidentified data can be re-identified using genetic information, credit information, etc., and personal health information can be abused as sensitive information. In this paper, we derive the need for homomorphic encryption to protect the privacy of personal information separated by sensitive information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3699-3719
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• 2017

Conjunctive keyword search encryption is an important technique for protecting sensitive personal health records that are outsourced to cloud servers. It has been extensively employed for cloud storage, which is a convenient storage option that saves bandwidth and economizes computing resources. However, the process of searching outsourced data may facilitate the leakage of sensitive personal information. Thus, an efficient data search approach with high security is critical. The multi-user search function is critical for personal health records (PHRs). To solve these problems, this paper proposes a novel multi-user conjunctive keyword search scheme (mNCKS) without a secure channel against keyword guessing attacks for personal health records, which is referred to as a secure channel-free mNCKS (SCF-mNCKS). The security of this scheme is demonstrated using the Decisional Bilinear Diffie-Hellman (DBDH) and Decision Linear (D-Linear) assumptions in the standard model. Comparisons are performed to demonstrate the security advantages of the SCF-mNCKS scheme and show that it has more functions than other schemes in the case of analogous efficiency.

• Smart Media Journal
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• v.8 no.1
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• pp.9-18
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• 2019

In the era of the 4th industrial revolution, the big data industry is gathering attention for new business models in the public and private sectors by utilizing various information collected through the internet and mobile. However, although the big data integration and analysis are performed with de-identification techniques, there is still a risk that personal privacy can be exposed. Recently, there are many studies to invent effective methods to maintain the value of data without disclosing personal information. In this paper, a personal information protection system is investigated to boost big data utilization in industrial sectors, such as healthcare and agriculture. The criteria for evaluating the de-identification adequacy of personal information and the protection scope of personal information should be differently applied for each industry. In the field of personal sensitive information-oriented healthcare sector, the minimum value of k-anonymity should be set to 5 or more, which is the average value of other industrial sectors. In agricultural sector, it suggests the inclusion of companion dogs or farmland information as sensitive information. Also, it is desirable to apply the demonstration steps to each region-specific industry.