• Title/Summary/Keyword: Internet privacy

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The Impact of Privacy Control on Users' Intention to Use Smart Home Internet of Things (IoT) Services

  • Kim, Mingyung;Choi, Bo Reum
    • Asia Marketing Journal
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    • v.24 no.1
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    • pp.29-38
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    • 2022
  • Despite the diverse benefits of smart home Internet of Things (IoT) services, the biggest obstacle to the actual usage of those services is concern about privacy. However, little research has investigated the impact of privacy control on users' intention to use smart home services. Based on communication privacy management theory and privacy calculus theory, this study investigates how privacy control options affect users' perceived benefits and costs and how those perceptions affect individuals' intentions to use smart home services by conducting an experiment. Our results showed that smart home privacy control options decreased perceived benefits and increased perceived costs. The perceived benefits and costs significantly affected the intention to use smart home security services. More intriguingly, the effect of perceived benefit was found to be stronger than that of the expected cost. This research contributes to the field of IoT and smart home research and provides practitioners with notable guidelines.

Clustering-Based Federated Learning for Enhancing Data Privacy in Internet of Vehicles

  • Zilong Jin;Jin Wang;Lejun Zhang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.6
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    • pp.1462-1477
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    • 2024
  • With the evolving complexity of connected vehicle features, the volume and diversity of data generated during driving continue to escalate. Enabling data sharing among interconnected vehicles holds promise for improving users' driving experiences and alleviating traffic congestion. Yet, the unintentional disclosure of users' private information through data sharing poses a risk, potentially compromising the interests of vehicle users and, in certain cases, endangering driving safety. Federated learning (FL) is a newly emerged distributed machine learning paradigm, which is expected to play a prominent role for privacy-preserving learning in autonomous vehicles. While FL holds significant potential to enhance the architecture of the Internet of Vehicles (IoV), the dynamic mobility of vehicles poses a considerable challenge to integrating FL with vehicular networks. In this paper, a novel clustered FL framework is proposed which is efficient for reducing communication and protecting data privacy. By assessing the similarity among feature vectors, vehicles are categorized into distinct clusters. An optimal vehicle is elected as the cluster head, which enhances the efficiency of personalized data processing and model training while reducing communication overhead. Simultaneously, the Local Differential Privacy (LDP) mechanism is incorporated during local training to safeguard vehicle privacy. The simulation results obtained from the 20newsgroups dataset and the MNIST dataset validate the effectiveness of the proposed scheme, indicating that the proposed scheme can ensure data privacy effectively while reducing communication overhead.

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.

Developing the online reviews based recommender models for multi-attributes using deep learning (딥러닝을 이용한 온라인 리뷰 기반 다속성별 추천 모형 개발)

  • Lee, Ryun-Kyoung;Chung, Namho;Hong, Taeho
    • The Journal of Information Systems
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    • v.28 no.1
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    • pp.97-114
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    • 2019
  • Purpose The purpose of this study is to deduct the factors for explaining the economic behavior of an Internet user who provides personal information notwithstanding the concern about an invasion of privacy based on the Information Privacy Calculus Theory and Communication Privacy Management Theory. Design/methodology/approach This study made a design of the research model by integrating the factors deducted from the computation theory of information privacy with the factors deducted from the management theory of communication privacy on the basis of the Dual-Process Theory. Findings According to the empirical analysis result, this study confirmed that the Privacy Concern about forms through the Perceived Privacy Risk derived from the Disposition to value Privacy. In addition, this study confirmed that the behavior of an Internet user involved in personal information offering occurs due to the Perceived Benefits contradicting the Privacy Concern.

A Study on Privacy Attitude and Protection Intent of MyData Users: The Effect of Privacy cynicism (마이데이터 이용자의 프라이버시 태도와 보호의도에 관한 연구: 프라이버시 냉소주의의 영향)

  • Jung, Hae-Jin;Lee, Jin-Hyuk
    • Informatization Policy
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    • v.29 no.2
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    • pp.37-65
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    • 2022
  • This article analyzes the relationship between the privacy attitudes of MyData users and the four dimensions of privacy cynicism (distrust, uncertainty, powerlessness, and resignation) as to privacy protection intentions through a structural equation model. It was examined that MyData user's internet skills had a statistically significant negative effect on 'resignation' among the privacy cynicism dimensions. Secondly, privacy risks have a positive effect on 'distrust' in MyData operators, 'uncertainty' in privacy control, and 'powerlessness' in terms of privacy cynicism. Thirdly, it was analyzed that privacy concerns have a positive effect on the privacy cynicism dimensions of 'distrust' and 'uncertainty', with 'resignation' showing a negative effect. Fourthly, it was found that only 'resignation' as a dimension of privacy cynicism showed a negative effect on privacy protection intention. Overall, MyData user's internet skills was analyzed as a variable that could alleviate privacy cynicism. Privacy risks are a variable that reinforces privacy cynicism, and privacy concerns reinforce privacy cynicism. In terms of privacy cynicism, 'resignation' offsets privacy concerns and lowers privacy protection intentions.

A Cache Privacy Protection Mechanism based on Dynamic Address Mapping in Named Data Networking

  • Zhu, Yi;Kang, Haohao;Huang, Ruhui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.6123-6138
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    • 2018
  • Named data networking (NDN) is a new network architecture designed for next generation Internet. Router-side content caching is one of the key features in NDN, which can reduce redundant transmission, accelerate content distribution and alleviate congestion. However, several security problems are introduced as well. One important security risk is cache privacy leakage. By measuring the content retrieve time, adversary can infer its neighbor users' hobby for privacy content. Focusing on this problem, we propose a cache privacy protection mechanism (named as CPPM-DAM) to identify legitimate user and adversary using Bloom filter. An optimization for storage cost is further provided to make this mechanism more practical. The simulation results of ndnSIM show that CPPM-DAM can effectively protect cache privacy.

Quantizing Personal Privacy in Ubiquitous Computing

  • Ma, Tinghuai;Tian, Wei;Guan, Donghai;Lee, Sung-Young
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.9
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    • pp.1653-1667
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    • 2011
  • Privacy is one of the most important and difficult research issues in ubiquitous computing. It is qualitative rather than quantitative. Privacy preserving mainly relies on policy based rules of the system, and users cannot adjust their privacy disclosure rules dynamically based on their wishes. To make users understand and control their privacy measurement, we present a scheme to quantize the personal privacy. We aim to configure the person's privacy based on the numerical privacy level which can be dynamically adjusted. Instead of using the traditional simple rule engine, we implement this scheme in a complex way. In addition, we design the scenario to explain the implementation of our scheme. To the best of our knowledge, we are the first to assess personal privacy numerically to achieve precision privacy computing. The privacy measurement and disclosure model will be refined in the future work.

A Comparative Study of the Effects of Consumer Innovativeness, Self-esteem, and Need for Cognition on Online Activity before and after COVID-19

  • Myung Gwan Lee;Sang Hyeok Park;Seung Hee Oh
    • Journal of Information Technology Applications and Management
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    • v.30 no.5
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    • pp.121-139
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    • 2023
  • This study tried to identify factors affecting online activity before and after the COVID-19 pandemic. To this end, the effects of consumer innovativeness, self-esteem, and need for cognition on the activity of online media such as Internet and social media were investigated, and whether privacy concerns had a moderating effect. For this study, survey data from 2019(before the outbreak of COVID-19) to 2021(after the outbreak of COVID-19) of the 'Korea Media Panel Survey' surveyed by the Korea Information Society Development Institute was used for analysis. The research results that affect Internet activity are as follows. Before the outback of COVID-19, it was found that hedonic innovativeness and social innovativeness had a positive effect and cognitive innovativeness had a negative effect on increasing Internet activity. There was no moderating effect on privacy concerns. The period after the outbreak of COVID-19, need for cognition was found to have a positive effect on increasing social media activity. In addition, the moderating effect of privacy concerns was found in the relationship between need for cognition and Internet activity. There was no privacy concern effect before the outbreak of COVID-19, and the privacy concern effect appeared on functional innovation and need for cognition after the outbreak of COVID-19. This study aims to present various implications for companies to understand the characteristics of online consumers using the Internet and social media after the pandemic.

A Study on Factors Influencing Privacy Decision Making on the Internet: Focus on Dual-Calculus Model (온라인 환경에서 프라이버시 의사결정에 영향을 미치는 요인에 관한 연구: 이중계산모델을 중심으로)

  • Kim, Sanghee;Kim, Jongki
    • The Journal of Information Systems
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    • v.25 no.3
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    • pp.197-215
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    • 2016
  • Purpose This study aims to investigate the factors that influence decision making in relation to providing personal information on the internet with respect to the integration of the privacy calculus theory and protection motivation theory based on the dual-calculus model proposed by Li(2012). Design/methodology/approach The privacy calculus theory and protection motivation theory have been applied to explain privacy behavior to a certain degree but few studies have been conducted to explain privacy behavior based on the integration of these two theories. Although Li(2012) proposed the dual-calculus model, he only proposed its framework and did not carry out an empirical study. Therefore, this study proposes a research model that integrates these two theories and examines the relationship between the two theories through an empirical study. Findings According to the results of empirical analysis, it was found that all relations have statistically significant explanatory power except the relation between coping appraisal and privacy risk in the risk calculus process. Thus, the results verify that external threat played a decisive role in increasing the risk level of a consumer's privacy. It can be discussed the ways to enhance the privacy behavior of consumer on the internet through these findings.

Securing Anonymous Authenticated Announcement Protocol for Group Signature in Internet of Vehicles

  • Amir, Nur Afiqah Suzelan;Malip, Amizah;Othman, Wan Ainun Mior
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.11
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    • pp.4573-4594
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    • 2020
  • Announcement protocol in Internet of Vehicles (IoV) is an intelligent application to enhance public safety, alleviate traffic jams and improve transportation quality. It requires communication between vehicles, roadside units and pedestrian to disseminate safety-related messages. However, as vehicles connected to internet, it makes them accessible globally to a potential adversary. Safety-related application requires a message to be reliable, however it may intrude the privacy of a vehicle. Contrarily, if some misbehaviour emerges, the malicious vehicles must be able to traceable and revoke from the network. This is a contradiction between privacy and accountability since the privacy of a user should be preserved. For a secure communication among intelligent entities, we propose a novel announcement protocol in IoV using group signature. To the best of our knowledge, our work is the first comprehensive construction of an announcement protocol in IoV that deploys group signature. We show that our protocol efficiently solves these conflicting security requirements of message reliability, privacy and accountability using 5G communication channel. The performance analysis and simulation results signify our work achieves performance efficiency in IoV communication.