• Title/Summary/Keyword: 온라인 프라이버시

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Moderating Effect of Security Ability on the Relation between Privacy Concern and Internet Activities

  • Hong, Jae-Won
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.1
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    • pp.151-157
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    • 2020
  • This study explored the moderating effects of security ability on the influence of privacy concerns on internet activity using Korea media panel survey data. To this end, we applied between-subjects factorial design between 2 (privacy concern high / low) × 2 (security ability high / low) groups and compared five types of internet activity among four groups by variance analysis. As a result, privacy concerns have a main effect on internet activity, and security ability have a moderating role in this relationship. Despite the privacy concerns, people do their internet activities in order to enjoy the benefit from the internet. This study have academic implication in that it focus on the issue of privacy paradox in terms of the type of internet activity. In addition, practical implications are that, in order to activate online activities of individuals in an internet-connected society, efforts for enhancing their security abilities are necessary.

A Model for Privacy Preserving Publication of Social Network Data (소셜 네트워크 데이터의 프라이버시 보호 배포를 위한 모델)

  • Sung, Min-Kyung;Chung, Yon-Dohn
    • Journal of KIISE:Databases
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    • v.37 no.4
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    • pp.209-219
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    • 2010
  • Online social network services that are rapidly growing recently store tremendous data and analyze them for many research areas. To enhance the effectiveness of information, companies or public institutions publish their data and utilize the published data for many purposes. However, a social network containing information of individuals may cause a privacy disclosure problem. Eliminating identifiers such as names is not effective for the privacy protection, since private information can be inferred through the structural information of a social network. In this paper, we consider a new complex attack type that uses both the content and structure information, and propose a model, $\ell$-degree diversity, for the privacy preserving publication of the social network data against such attacks. $\ell$-degree diversity is the first model for applying $\ell$-diversity to social network data publication and through the experiments it shows high data preservation rate.

A Study on Anonymity for Privacy Protection in SNS Environments (SNS 환경에서의 프라이버시 보호를 위한 익명성 보장에 관한 연구)

  • Kim, Jun-Sub;Kwak, Jin
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.05a
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    • pp.576-579
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    • 2013
  • SNS는 온라인상에서 특정한 관심이나 활동을 공유하는 사람들 또는 불특정 타인과 관계망을 맺을 수 있는 서비스이다. 사회적 관계를 맺고 친분 관계를 유지해주는 SNS 서비스가 활발하게 이용되고 있는 반면에 SNS 사용자들에 대한 프라이버시가 노출되는 문제가 발생하고 있다. 따라서 본 논문에서는 SNS 환경에서의 프라이버시 보호를 위한 익명성 보장 방법에 대하여 제안한다. 본 제안사항은 사용자가 프라이버시 설정 단계를 통해 설정한 프라이버시에 따라 자신의 프로파일 정보 및 게시물 정보를 친구 또는 다른 사용자들이 확인하거나 익명성을 보장할 수 있다.

Analysis and Proposal of "Do Not Track" Regulations for Online Behavioral Advertising (온라인 행동기반 맞춤형 광고를 위한 온라인 추적 금지 제도 분석 및 제안)

  • Choi, Jinju;Lee, Chunghun;Kim, Beomsoo
    • The Journal of Society for e-Business Studies
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    • v.17 no.4
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    • pp.155-174
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    • 2012
  • As Online Behavioral Advertising is dramatically growing with usefulness of information and user convenience in recent years, there are privacy issues caused by collecting user's behavioral information without their consent. To tackle the problem, the need of Do Not Track regulations is getting much higher. In Korea, however, it has never existed. So, this study is examining the case of the major countries have been enforcing the law and regulations of DNT. After that, it is classified with four domain (law/regulation, corporation, individual, society) to include all stakeholders of OBA. Furthermore, this study may have academic significance by suggesting DNT framework through analysis of them. Providing DNT mechanism consisted of three type (behavioral information, control, DNT system), it can be useful guidelines for companies to support decision making as introduced DNT. As analyzed between DNT and stakeholders based on the study of OBA market, it will be useful basic material of OBA study later.

How Consumers Perceive Online Behavioral Advertising: Consumer Typology and Determining Factors (온라인 맞춤형 광고 인식에 따른 소비자유형 연구: 효용과 비용을 중심으로)

  • Lee, Jin-Myong;Rha, Jong-Youn
    • Journal of Digital Convergence
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    • v.13 no.9
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    • pp.105-114
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    • 2015
  • This study aims 1) to identify distinctive consumer groups according to their perception of benefits and costs of Online Behavioral Advertising(OBA), 2) to explore differences among them, and 3) to investigate antecedent variables that affect the consumers' perception of OBA. Online survey data collected from 1,000 online users. The findings of this study are as follows. First, the result of cluster analysis identified four distinctive consumer groups according to the levels of perceived benefits and costs of OBA: 'Indifferent group', 'cost-centered group', 'benefit-centered group', and 'Benefit-cost balanced group'. Second, four consumer groups showed differences in their demographics, advertising related variables, privacy related variables, and technology related variables. Third, according to multinomial logistic analysis, it was found that there were different factors affecting consumers' perception of benefits and costs of OBA.

테마연재 / 온라인 프라이버시 침해 증가 .. 소비자 정보 보호 필요

  • Kim, Yeon-Su
    • Digital Contents
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    • no.1 s.116
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    • pp.84-99
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    • 2003
  • 본고를 통해 일반적으로 소비자, 이용자·네티즌 등의 법적의미와 온라인 사업자로 지칭되는 인터넷 기타 정보통신관련 사업자들의 법률 적용 범위를 명확히 함으로써 사업자, 전기통신사업자, 정보통신서비스제공자, 전자거래 사업자, 전자상거래 사업자, 통신판매업자의 관계를 관련 특별법을 통해 비교,분석해 그 정의와 법적 범위를 분명히 하는데 일조하고자 한다. 또한 이러한 관계에서 정보주체의 개인정보 도용사례를 기술적 과정과 동향을 통해 구체적으로 살펴보기로 한다.

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A Study on the Privacy Awareness through Bigdata Analysis (빅데이터 분석을 통한 프라이버시 인식에 관한 연구)

  • Lee, Song-Yi;Kim, Sung-Won;Lee, Hwan-Soo
    • Journal of Digital Convergence
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    • v.17 no.10
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    • pp.49-58
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    • 2019
  • In the era of the 4th industrial revolution, the development of information technology brought various benefits, but it also increased social interest in privacy issues. As the possibility of personal privacy violation by big data increases, academic discussion about privacy management has begun to be active. While the traditional view of privacy has been defined at various levels as the basic human rights, most of the recent research trends are mainly concerned only with the information privacy of online privacy protection. This limited discussion can distort the theoretical concept and the actual perception, making the academic and social consensus of the concept of privacy more difficult. In this study, we analyze the privacy concept that is exposed on the internet based on 12,000 news data of the portal site for the past one year and compare the difference between the theoretical concept and the socially accepted concept. This empirical approach is expected to provide an understanding of the changing concept of privacy and a research direction for the conceptualization of privacy for current situations.

A Consumer Perception based on the Type of Recommender System : A Privacy Calculus Perspective (상품 추천 서비스 유형에 따른 소비자 반응 연구 : 프라이버시 계산 모델을 중심으로)

  • Choi, Hye-Jin;Cho, Chang-Hoan
    • The Journal of the Korea Contents Association
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    • v.20 no.3
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    • pp.254-266
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    • 2020
  • The purpose of this study is to analyze the influence of the type of recommender system on consumer's perceived benefit and privacy risk. The result showed that the perceived usefulness and intension to click was high in the order of Hybrid-filtering, Bestseller, and SNS-based system. Privacy concern was high in order of SNS-based system, Hybrid-filtering, and Bestseller. Moderating effects of perceived personalization on the type of recommender system and perceived usefulness were significant. Finally perceived usefulness had positive effect, and privacy concern had negative effect on consumer's intension to click. This study has significant implications for digital marketing bt comparing consumer responses according to the type of recommended service. The result of this study can be helpful for providing and developing future recommender service.

Differential Privacy Technology Resistant to the Model Inversion Attack in AI Environments (AI 환경에서 모델 전도 공격에 안전한 차분 프라이버시 기술)

  • Park, Cheollhee;Hong, Dowon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.3
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    • pp.589-598
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    • 2019
  • The amount of digital data a is explosively growing, and these data have large potential values. Countries and companies are creating various added values from vast amounts of data, and are making a lot of investments in data analysis techniques. The privacy problem that occurs in data analysis is a major factor that hinders data utilization. Recently, as privacy violation attacks on neural network models have been proposed. researches on artificial neural network technology that preserves privacy is required. Therefore, various privacy preserving artificial neural network technologies have been studied in the field of differential privacy that ensures strict privacy. However, there are problems that the balance between the accuracy of the neural network model and the privacy budget is not appropriate. In this paper, we study differential privacy techniques that preserve the performance of a model within a given privacy budget and is resistant to model inversion attacks. Also, we analyze the resistance of model inversion attack according to privacy preservation strength.