• 디지털융복합연구
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• 제17권11호
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• pp.127-136
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• 2019

소셜 미디어 사용자들이 서비스 업체에 공유하는 정보는 성별, 나이와 같은 개인 식별 정보와 사진, 댓글과 같은 사생활 정보로 구분할 수 있다. 하지만 기존 소셜 미디어 관련 연구들에서는 정보 유형에 따른 의사 결정 차이가 생길 수 있음에도 불구하고 두 정보 유형을 구분하여 정보 공유 의사 결정 차이를 살펴본 연구는 미흡하였다. 그래서 본 연구에서는 정보 유형에 따른 정보 공유 의사 결정 차이를 살펴보고자 한다. 350명의 페이스북 사용자를 대상으로 연구 모형을 분석하였다. 연구 모형 분석 결과, 자기 표현, 신뢰, 인지된 보안은 개인 식별 정보 의지와 사생활 정보 공유 의지 모두에 양으로 유의한 영향을 미쳤다. 하지만, 프라이버시 침해 우려는 개인 식별 정보 의지와 사생활 정보 공유 의지에 부정적으로 유의한 영향을 미쳤다. 본 연구 결과를 통해 개인 정보 공유에 대한 의사 결정과 사생활 정보 공유에 대한 의사 결정이 차이가 없음을 확인할 수 있었다.

• 디지털융복합연구
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• 제17권7호
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• pp.285-292
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• 2019

PC, SNS, IoT의 대중화로 수많은 데이터가 생성되고 그 양은 기하급수적으로 증가하고 있다. 거대한 양의 데이터를 활용하는 방법으로 인공신경망 학습은 최근 많은 분야에서 주목받는 주제이다. 인공신경망 학습은 음성인식, 이미지 인식에서 엄청난 잠재력을 보였으며 더 나아가 의료진단, 인공지능 게임 및 얼굴인식 등 다양하고 복잡한 곳에 광범위하게 적용된다. 인공신경망의 결과는 실제 인간을 능가할 정도로 정확성을 보이고 있다. 이러한 많은 이점에도 불구하고 인공신경망 학습에는 여전히 프라이버시 문제가 존재한다. 인공신경망 학습을 위한 학습 데이터에는 개인의 민감한 정보를 포함한 다양한 정보가 포함되어 악의적인 공격자로 인해 프라이버시가 노출될 수 있다. 공격자가 학습하는 도중 개입하여 학습이 저하되거나 학습이 완료된 모델을 공격할 때 발생하는 프라이버시 위험이 있다. 본 논문에서는 최근 제안된 신경망 모델의 공격 기법과 그에 따른 프라이버시 보호 방법을 분석한다.

• 경영과학
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• 제29권2호
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• pp.1-20
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• 2012

While feeling anxious about the risk of exposure of personal information and privacy, users of microblogs and social network services are continuously using them. This study aims to develop a model to investigate this phenomenon. Specifically, this study explores the relationship between personal characteristics (represented by privacy concern and self-presentation) and an individual's self-disclosure. An individual's personal belief (represented by perceived risk and perceived trust) is also tested as an mediator between the relationship. Through a questionnaire survey to 183 twitter users in Korea, the results indicate that self-presentation has a direct influence on self-disclosure as well as an indirect influence through perceived trust. In contrast, privacy concern has not a direct but an indirect negative influence on self-disclosure through perceived risk. In conclusion, self-presentation has a stronger influence on self-disclosure then privacy concern to Twitter users. An individual who has a higher propensity for self-presentation will form a stronger perceived trust on Twitter, which in turn, affects the individual's self-disclosure. On the other hand, an individual who is more concerned with personal privacy will feel more serious about perceived risk, which in turn, negatively influences one's perception of the trust in Twitter as well as his desire for self-disclosure.

• 지식경영연구
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• 제18권1호
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• pp.159-176
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• 2017

Recently, the popularity of smartphones has led to a dramatic increase in the frequency of use of App(Application) services. LBS (Location-Based Service) App service adopts various methods such as push marketing and useful information by region through providing location-based service based on the location of the consumer. In particular, an enterprise or an App management company can provide necessary information to the consumer through the necessary information among the customer related knowledge information obtained by utilizing the location information of the consumer in real time. Nevertheless, since LBS is a service that can be performed only when the company obtains consent to provide location information voluntarily by the consumer, there is a case of privacy infringement due to consumers' use of personal information. The purpose of this study is to identify the characteristics of privacy related variables and the knowledge structure for consumer value formation based on the theory of privacy calculation. We also compared the characteristics of Korea with those of China in privacy issue. As a result of the analysis, it was confirmed that factors such as information utilization ability and information control ability were influential as a key factor of privacy calculation. In addition, perceived value influences the reputation of the LBS App service.

• 한국통신학회논문지
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• 제30권10B호
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• pp.648-659
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• 2005

인터넷에 산재되어 있는 사용자 개인정보의 오남용은 더 이상 간과할 수 없는 문제이다. 개인정보의 유통은 반드시 소유자의 허가 하에서만 이루어져야 하고, 개인정보를 관리하는 사이트는 인터넷에 익숙하지 않은 사용자들에게 개인정보 유출에 관한 두려움을 없애줄 수 있는 환경을 제공하여야 한다. 본 논문은 인터넷 Identity 관리시스템에서 개인정보를 안전하게 관리하고 유통할 수 있는 기술을 소개한다. 개인정보의 소유자가 자신의 정보를 관리하는 방법, 정보 관리 시스템 차원에서 사용자 정보를 관리하기 위한 정책, 개인정보 접근을 제어하는 Privacy Controller 등 여러 관점에서의 프라이버시 인가 기술을 제안한다. 그리고, 정책 기반의 프라이버시 인가 기술을 인터넷 Identity 관리 시스템에 적용하기 위한 다양한 모델을 제시한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권6호
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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.

• 아태비즈니스연구
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• 제15권2호
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• pp.107-123
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• 2024

Purpose - This study aims to analyze the relationship between perceived risk, privacy concerns, continual intention to use of Fintech services. Design/methodology/approach - This research developed a conceptual framework using attitude theory and analyzed the relationship between risk perception to Fintech services, Fintech concerns(service concern, platform concern, network concern, device concern, and privacy concern), and continual use in the context of Fintech services. In this study, Data analyzed using the PLS(partial least squares) structural equation model approach. Findings - As a result of empirical analysis, Fintech risk perception affected service concern, platform concern, network concern, device concern, and privacy concern. In addition, it was found that privacy risk did not affect continual use of Fintech services. In addition, among Fintech service concerns, platform concern, network concern, and privacy concern did not affect continual use of Fintech services. However, only device concern affected the intention to continual use of Fintech services. Research implications or Originality - The results will help to understand the psychology of Fintech service users and develop more stable Fintech services continual use strategies.

• Journal of Computing Science and Engineering
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• 제2권2호
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• pp.137-160
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• 2008

The increasing availability of personal location data pushed by the widespread use of location-sensing technologies raises concerns with respect to the safeguard of location privacy. To address such concerns location privacy-preserving techniques are being investigated. An important area of application for such techniques is represented by Location Based Services (LBS). Many privacy-preserving techniques designed for LBS are based on the idea of forwarding to the LBS provider obfuscated locations, namely position information at low spatial resolution, in place of actual users' positions. Obfuscation techniques are generally based on the use of geometric methods. In this paper, we argue that such methods can lead to the disclosure of sensitive location information and thus to privacy leaks. We thus propose a novel method which takes into account the semantic context in which users are located. The original contribution of the paper is the introduction of a comprehensive framework consisting of a semantic-aware obfuscation model, a novel algorithm for the generation of obfuscated spaces for which we report results from an experimental evaluation and reference architecture.

• 한국멀티미디어학회논문지
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• 제12권12호
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• pp.1796-1808
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• 2009

Elementary school students have a little awareness of privacy protection since they do not have many opportunities for systematic education on information and communication ethics. Hence, they are likely to expose their own information to others and sometimes bring on a lot of misuses by using others' information. In this paper, we provide an idea for teaching and learning methods which the elementary school students acquire privacy protection and management methods and raise their practical capabilities. We develop a role play teaching and learning model in connection with various Information and Communication Technology (ICT) activities and establish the instruction plans. Moreover, we apply them to the actual classes at grade five and six of the elementary school students respectively, and finally analyze the results. The proposed teaching and learning method shows that the students participated in a series of learning activities have higher learning effects on awareness of privacy protection than those learned with the conventional methods.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 2003년도 하계학술대회논문집
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• pp.245-248
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• 2003

LBS는 이동통신망이나 위성신호등을 이용하여 Mobile 단말의 위치를 측정하고, 측정한 위치와 관련된 다양한 정보 서비스를 제공하기 위한 기술이다. 그러나 사용자의 프라이버시(Privacy) 문제나 접근제어(Access Control)같은 인증(Authentication)문제가 중요한 이슈로 대두되고 있다. 본 논문에서는 LBS에 대한 전반적인 사항을 분석하여 문제점을 도출하고, LBS Privacy 문제점을 보호할 수 있는 방안을 제시한다. 최종적으로 제안된 모델은 차세대 LBS 시스템의 개인정보 및 Privacy 보호를 위한 기술적인 대안을 제시하였으며, 차세대 이동통신의 기반 기술이 될 것으로 기대한다.