• 제목/요약/키워드: Personal data

검색결과 5,505건 처리시간 0.031초

공공데이터 활용성 제고를 위한 권리처리 플랫폼 구축 전략 (Strategy for Establishing a Rights Processing Platform to Enhance the Utilization of Open Data)

  • 심준보;권헌영
    • 한국IT서비스학회지
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    • 제21권3호
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    • pp.27-42
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    • 2022
  • Open Data is an essential resource for the data industry. 'Act On Promotion Of The Provision And Use Of Public Data', enacted on July 30, 2013, mandates public institutions to manage the quality of Open Data and provide it to the public. Via such a legislation, the legal basis for the public to Open Data is prepared. Furthermore, public institutions are prohibited from developing and providing open data services that are duplicated or similar to those of the private sector, and private start-ups using open data are supported. However, as the demand for Open Data gradually increases, the cases of refusal to provide or interruption of Open Data held by public institutions are also increasing. Accordingly, the 'Open Data Mediation Committee' is established and operated so that the right to use data can be rescued through a simple dispute mediation procedure rather than complicated administrative litigation. The main issues dealt with in dispute settlement so far are usually the rights of third parties, such as open data including personal information, private information such as trade secrets, and copyrights. Plus, non-open data cannot be provided without the consent of the information subject. Rather than processing non-open data into open data through de-identification processing, positive results can be expected if consent is provided through active rights processing of the personal information subject. Not only can the Public Mydata Service be used by the information subject, but Open Data applicants will also be able to secure higher quality Open Data, which will have a positive impact on fostering the private data industry. This study derives a plan to establish a rights processing platform to enhance the usability of Open Data, including private information such as personal information, trade secrets, and copyright, which have become an issue when providing Open Data since 2014. With that, the proposals in this study are expected to serve as a stepping stone to revitalize private start-ups through the use of wide Open Data and improve public convenience through Public MyData services of information subjects.

사물인터넷(IoT) 환경에서의 개인정보 위험 분석 프레임워크 (Risk Analysis for Protecting Personal Information in IoT Environments)

  • 이애리;김범수;장재영
    • 한국IT서비스학회지
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    • 제15권4호
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    • pp.41-62
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    • 2016
  • In Internet of Things (IoT) era, more diverse types of information are collected and the environment of information usage, distribution, and processing is changing. Recently, there have been a growing number of cases involving breach and infringement of personal information in IoT services, for examples, including data breach incidents of Web cam service or drone and hacking cases of smart connected car or individual monitoring service. With the evolution of IoT, concerns on personal information protection has become a crucial issue and thus the risk analysis and management method of personal information should be systematically prepared. This study shows risk factors in IoT regarding possible breach of personal information and infringement of privacy. We propose "a risk analysis framework of protecting personal information in IoT environments" consisting of asset (personal information-type and sensitivity) subject to risk, threats of infringement (device, network, and server points), and social impact caused from the privacy incident. To verify this proposed framework, we conducted risk analysis of IoT services (smart communication device, connected car, smart healthcare, smart home, and smart infra) using this framework. Based on the analysis results, we identified the level of risk to personal information in IoT services and suggested measures to protect personal information and appropriately use it.

Personal Data Security in Recruitment Platforms

  • Bajoudah, Alya'a;AlSuwat, Hatim
    • International Journal of Computer Science & Network Security
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    • 제22권6호
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    • pp.310-318
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    • 2022
  • Job offers have become more widespread and it has become easier and faster to apply for jobs through electronic recruitment platforms. In order to increase the protection of the data that is attached to the recruitment platforms. In this research, a proposed model was created through the use of hybrid encryption, which is used through the following algorithms: AES,Twofish,. This proposed model proved the effectiveness of using hybrid encryption in protecting personal data.

IoT 환경에서 GDPR에 부합하는 개인정보수집 동의 절차 (GDPR Compliant Consent Procedure for Personal Information Collection in the IoT Environment)

  • 이구연;방준일;차경진;김화종
    • 한국정보기술학회논문지
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    • 제17권5호
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    • pp.129-136
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    • 2019
  • 센서 등 많은 IoT 디바이스들은 화면출력 및 입력장치 등이 결여된 경우가 많아 개인정보보호법이나 GDPR 등에서 요구하는 개인정보수집 동의 절차를 만족시키기 어려워, 해당 비즈니스 분야 발전에 법적인 걸림돌로 작용하고 있다. 본 연구에서는 법적인 요건을 만족하는 IoT 시스템에서의 개인정보수집 동의 절차를 설계한다. 설계된 방식에서는 먼저 사용자의 개인정보가 암호화된 상태로 수집되며, 이후 데이터 수집 서버와 사용자 에이전트 사이에 개인정보 수집을 기반으로 연관을 맺음으로서 암호화된 내용을 복호화 한다. 이러한 연관 동의 과정에서 사용자 에이전트는 데이터 수집 서버의 개인정보수집 약관 등을 이해하고 복호화키를 제공한다. IoT 시스템에서의 이러한 방식의 개인정보수집 동의 절차는 GDPR 등의 법령에서 정하는 투명성, 자율성 등의 요건을 만족함으로서 개인정보를 취급하는 IoT 비지니스 분야의 발전에 크게 기여할 것으로 판단된다.

Privacy-Preserving Deep Learning using Collaborative Learning of Neural Network Model

  • Hye-Kyeong Ko
    • International journal of advanced smart convergence
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    • 제12권2호
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    • pp.56-66
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    • 2023
  • The goal of deep learning is to extract complex features from multidimensional data use the features to create models that connect input and output. Deep learning is a process of learning nonlinear features and functions from complex data, and the user data that is employed to train deep learning models has become the focus of privacy concerns. Companies that collect user's sensitive personal information, such as users' images and voices, own this data for indefinite period of times. Users cannot delete their personal information, and they cannot limit the purposes for which the data is used. The study has designed a deep learning method that employs privacy protection technology that uses distributed collaborative learning so that multiple participants can use neural network models collaboratively without sharing the input datasets. To prevent direct leaks of personal information, participants are not shown the training datasets during the model training process, unlike traditional deep learning so that the personal information in the data can be protected. The study used a method that can selectively share subsets via an optimization algorithm that is based on modified distributed stochastic gradient descent, and the result showed that it was possible to learn with improved learning accuracy while protecting personal information.

A Study on Strengthening Domestic Personal Information Impact Assessment(PIA)

  • Young-Bok Cho
    • 한국컴퓨터정보학회논문지
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    • 제29권6호
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    • pp.61-67
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    • 2024
  • 본 논문에서는 개인정보 영향평가의 법적 준거성을 확보하고 개인정보 영향평가 시 프라이버시 강화 방안을 제시함으로써 개인정보 유출 사고를 방지할 수 있는 강화 방안을 제시하였다. 최근 빅데이터를 기반으로 한 다양한 서비스들이 생성되면서 EU의 GDPR, 국내는 개인정보 보호법을 중심으로 개인정보보호를 위해 노력하고 있다. 이런 사회 속에서 기업들은 최신기술을 기반으로 한 개인의 맞춤형 서비스를 제공하기 위해 개인정보를 위탁 처리하게 되는데, 이때 수탁사를 통해 개인정보 유출 문제가 심각하게 발생하고 있다. 따라서 수탁사들의 개인정보 사용에 따른 법적 준거성을 확보하면서 체계적으로 개인정보를 관리 할 수 있는 방안에 대해 고찰한다.

데이터 3법 개정에 따른 분쟁조정위원회 역할과 이슈분석 (The Role and Issue analysis of the ADR's Committee in the Revision of Personal Information Protection Act)

  • 윤덕중;지윤석;김영애;신용태
    • 정보보호학회논문지
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    • 제30권2호
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    • pp.279-286
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    • 2020
  • 4차 산업혁명의 핵심 자원인 데이터의 융합과 활용을 촉진하여 데이터 산업의 발전을 지원하기 위해 2020년 2월 4일 「개인정보 보호법」이 개정 되었다. 법에서 적용하는 범위가 통신사업자와 금융사업자는 물론 개인정보 처리 사업자까지 늘어남에 따라 관련된 분쟁조정의 범위도 늘어날 것으로 보인다. 이에 본 논문에서는 개인정보 분쟁위원회의 역할·기능과 개인정보 분쟁조정의 제도적 기준에 대한 소개를 먼저하고, 개인정보 분쟁조정위원회가 데이터 3법개정에 따라 앞으로 해야 할 이슈에 대해 연구해 보았다. 이번 연구에서는 개인정보 분쟁조정에 대한 효율적인 운영을 위해 분야별 전문가 심의, 새로운 산업 기술에 대한 신규 조정기준, 개인정보 분쟁위원회와 개인정보위원회와의 업무연속성 확보방안, 조정결정과 법원간의 연계성 확보, 집단 분쟁 조정의 운영기준 강화 등을 제시하였다.

A Study on Family Variables and Personal Variables Affecting the Career Decision Level

  • Kim, Mi-Hyun;Choi, Yong-Seok
    • Journal of the Korean Data and Information Science Society
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    • 제18권4호
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    • pp.985-994
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    • 2007
  • We note that the time of adolescents is very important time for obtaining informations about their jobs, exploring and making appropriate their career decision. In order to understand the career decision level of adolescents, we needed a study on effects of personal variables and family variables affecting the career decision level. For this, we provide direct, indirect and total effects of family variables and personal variables on the career decision level using the path analysis. Therefore, in this study, we give the real usefulness for making a different diagnosis and strategy solving some problems of career decision level.

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Proactive Task Execution Using Data Sharing and Event Transition among Personal Devices

  • Jeon, Ho-Cheol;Kim, Tae-Hwan;Choi, Joong-Min
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제4권6호
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    • pp.1237-1252
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    • 2010
  • This paper proposes an intelligent technique for data sharing and event transition among personal devices including smart phones, laptops, and desktops. We implemented the PES (Personal Event Service) system that proactively executes appropriate tasks across multiple devices without explicit user requests by sharing the data used by the user and recognizing user intention based on the observed actions of the user for specific devices. The client module of PES installed on each device monitors the user actions and recognizes the intention of the user. The server provides data sharing and maintenance for clients. The connection between client and server is established by Java RMI (Remote Method Invocation). A series of experiments were performed to evaluate user satisfaction and system accuracy, and the results showed that the PES system can proactively provide appropriate, personalized services with a high degree of satisfaction to the user in an effective and efficient manner.

빅데이터 개인정보보호 가이드라인(안)의 개선 방향에 관한 연구 (A Study on the Improvements of the Big Data Guideline in Korea)

  • 김선남;이환수
    • 정보화정책
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    • 제21권4호
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    • pp.20-39
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    • 2014
  • 빅데이터 시대의 도래는 산업 발전에 대한 긍정적 시각과 함께 개인정보보호 및 프라이버시 침해와 관련한 우려 또한 낳고 있다. 이러한 상황에서 최근 방송통신위원회는 빅데이터 환경에서 개인정보 수집과 이용 범위를 규정하는 '빅데이터 가이드라인(안)'을 제시하였다. 그러나 동 '가이드라인(안)'은 산업 진흥에 목적을 두고 있어, 기존 "개인정보보호법"과 충돌하는 내용을 많이 포함하고 있는 상황이다. 이에 시민단체들은 정보주체의 인권이나 프라이버시를 침해할 수 있다는 이유로 제정을 강력히 반대하며, 결국 개인정보위원회는 최근 전면 재검토를 요청했다. 따라서 본 논문에서는 현 '가이드라인(안)'의 한계점을 분석하고, 국내 외 관련 법률을 검토하여, 개인정보보호를 통한 프라이버시 침해를 최소화하는 방향에서 기업들이 빅데이터를 안전하게 활용할 수 있도록 법과 제도적 정비 방안에 대해 논의한다.