• Title/Summary/Keyword: information privacy risk

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A Study on the Causal Relationship of Perceived Risks, Service Quality and Customer Satisfaction in Ubiquitous Environment by Using Spatial Information (유비쿼터스 환경에서 공간정보 활용에 따른 고객의 지각된 위험, 서비스 품질과 고객만족의 구조적 관계 연구)

  • Kim, Yong-Beom;Chung, Nam-Ho
    • Journal of the Korea Safety Management & Science
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    • v.10 no.3
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    • pp.145-154
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    • 2008
  • The Location Based Services (LBS) comprise spatial information and mobile technology allow users to receive various services based on Global Positioning Systems (GPS). Although, spatial information based services are very useful, it has lots of possibility to damage privacy protection. But the contents of the legislation by government have problems conflicted between protection of a person's location information and invigoration LBS. Therefore, in this study suggest a causal model to deal with user satisfaction and factors affecting spatial information based services to customer perspective. The proposed research model is tested empirically with one hundred and forty one usable questionnaires and partial least square (PLS) method. Experimental results showed that the usefulness, playfulness, and service quality play a prominent role in influencing the spatial information services satisfaction compared to other factors. But, easy of use and perceived risk are not significant.

A Study on the Causal Relationship of Perceived Risks, Service Quality and Customer Satisfaction in Ubiquitous Environment by Using Spatial Information (유비쿼터스 환경에서 공간정보 활용에 따른 고객의 지각된 위험, 서비스 품질과 고객만족의 구조적 관계 연구)

  • Chung, Nam-Ho;Kim, Yong-Bum
    • Proceedings of the Safety Management and Science Conference
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    • 2007.04a
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    • pp.373-385
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    • 2007
  • The Location Based Services (LBS) comprise spatial information and mobile technology allow users to receive various services based on Global Positioning Systems (GPS). Although, spatial information based services are very useful, it has lots of possibility to damage privacy protection. But the contents of the legislation by government have problems conflicted between protection of a person's location information and invigoration LBS. Therefore, in this study suggest a causal model to deal with user satisfaction and factors affecting spatial information based services to customer perspective. The proposed research model is tested empirically with one hundred and forty one usable questionnaires and partial least square (PLS) method. Experimental results showed that the usefulness, playfulness, and service quality play a prominent role in influencing the spatial information services satisfaction compared to other factors. But, easy of use and perceived risk are not significant.

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De-identification Techniques for Big Data and Issues (빅데이타 비식별화 기술과 이슈)

  • Woo, SungHee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.750-753
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    • 2017
  • Recently, the processing and utilization of big data, which is generated by the spread of smartphone, SNS, and the internet of things, is emerging as a new growth engine of ICT field. However, in order to utilize such big data, De-identification of personal information should be done. De-identification removes identifying information from a data set so that individual data cannot be linked with specific individuals. De-identification can reduce the privacy risk associated with collecting, processing, archiving, distributing or publishing information, thus it attempts to balance the contradictory goals of using and sharing personal information while protecting privacy. De-identified information has also been re-identified and has been controversial for the protection of personal information, but the number of instances where personal information such as big data is de-identified and processed is increasing. In addition, many de-identification guidelines have been introduced and a method for de-identification of personal information has been proposed. Therefore, in this study, we describe the big data de-identification process and follow-up management, and then compare and analyze de-identification methods. Finally we provide personal information protection issues and solutions.

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Factors Influencing on the Intention to Use Serious Games for Healthcare: The Perspective of Valence Framework (건강 기능성 게임의 수용에 영향을 주는 요인: 감정가 프레임워크 관점)

  • Yong-Young Kim
    • Journal of Information Technology Applications and Management
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    • v.31 no.1
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    • pp.97-112
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    • 2024
  • In order to verify the factors affecting the acceptance of Serious Games for Healthcare (SGHs), this study developed a hierarchical model of general and specific benefit and risk factors affecting the intention to use SGHs based on the valence framework. As a result based on 199 samples, it was revealed that perceived customization and perceived schedule flexibility had a positive effect on the perceived benefits, which, in turn, had a positive effect on the intention to use SGHs. However, among the specific risk factors, only privacy risk had a positive effect on perceived risk, but it did not have a effect on SGHs usage intention. The results related to the fact that the survey respondents were potential users of SGHs and the bias that may overestimate the benefits provided by SGHs called optimistic bias. Based on these findings, some implications were presented such as the spread and distribution of SGHs to the ordinary persons, improvement of negative perceptions of games, and the need for data-based services to refine customized services for SGHs.

An Empirical Study of the Effect of Perceived Risk upon Intention to LBS Use (위치기반서비스 이용에 대한 인지된 위험의 영향 연구)

  • Kim, Sang Min;Lee, Ji-Eun;Park, Chankwon
    • Journal of Digital Convergence
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    • v.12 no.12
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    • pp.119-127
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    • 2014
  • As the disclosure of privacy information has grown steadily, concerns about mobile services based on the personal information also increased. We aspired to reveal factors influencing the use of Location-Based services(LBS) App and analyse how the perceived risk affected between these factors and the use of LBS App. Results showed that usefulness and social influence influenced on the use of LBS App. We also found that the group who highly recognized the perceived risk was highly affected by usefulness and the group who lowly recognized the perceived risk was highly affected by social influence. Findings show that the company's strategy should be different depending on the level of consumers' perceived risk.

Perceived Usefulness and Risks and Behavioral Intentions of Mobile Fashion Apps -Focus Group Interviews with Chinese Students Studying in Korea- (모바일 패션 앱의 지각된 유용성과 위험 및 행동의도 -중국인 유학생 초점집단 면접 조사-)

  • Hong, Heesook;Sun, Yu;Lee, Seung-Eun
    • Journal of the Korean Society of Clothing and Textiles
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    • v.44 no.2
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    • pp.255-272
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    • 2020
  • This exploratory study investigated Chinese consumers' perceived usefulness and risks of fashion apps and identified reasons for continuance and discontinuance intentions. This study conducted focus group interviews with a convenience sample of 13 Chinese students majoring in fashion in Korea. Based on interviewee responses, this study identified five attributes leading the perceived usefulness of mobile fashion apps (ubiquity and convenience, multi-media information, personalization, interactivity between consumers, and immediateness) and sub elements related to the five attributes. Five types of perceived risk (privacy risk, security risk, product risk, loss of future opportunity, and time risk) were identified in relation to Chinese consumers' use of fashion apps. The important role of live streaming services was uniquely identified by Chinese fashion app users. Usefulness of location-based information provided by mobile fashion apps were differently perceived according to respondents' use purpose, and augmented reality services provided by the apps were related to entertainment rather than usefulness. This study provides meaningful insights into Chinese consumers' perceptions of fashion apps and important app attributes that influence their continuance and discontinuance intentions. The findings from this study lend preliminary implications for future researchers and fashion businesses interested in the Chinese app market.

Genetic Symmetric Key Generation for IDEA

  • Malhotra, Nandini;Nagpal, Geeta
    • Journal of Information Processing Systems
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    • v.11 no.2
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    • pp.239-247
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    • 2015
  • Cryptography aims at transmitting secure data over an unsecure network in coded version so that only the intended recipient can analyze it. Communication through messages, emails, or various other modes requires high security so as to maintain the confidentiality of the content. This paper deals with IDEA's shortcoming of generating weak keys. If these keys are used for encryption and decryption may result in the easy prediction of ciphertext corresponding to the plaintext. For applying genetic approach, which is well-known optimization technique, to the weak keys, we obtained a definite solution to convert the weaker keys to stronger ones. The chances of generating a weak key in IDEA are very rare, but if it is produced, it could lead to a huge risk of attacks being made on the key, as well as on the information. Hence, measures have been taken to safeguard the key and to ensure the privacy of information.

Factors Influencing Consumers' Actual Behavior based on Different Degree of Product Information (제품정보제공수준에 따른 소비자 행동)

  • Chang, Hwal-Sik;Park, Kwang-Oh;Wu, Zheng
    • The Journal of the Korea Contents Association
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    • v.10 no.6
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    • pp.175-187
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    • 2010
  • E-commerce has been developing rapidly by enabling companies to sell their products or services online. However, adoption of an e-commerce website still faces lots of problems, such as changing consumer behaviors from purchasing in physical stores to purchasing online, privacy and risk, and so on. The purpose of this study is to analyze the influence of consumers' attitude on actual purchasing behavior based on the degree of product information. In this study, we designed two kinds of product web pages which show different degrees of product information. The first web page has adequate product information, and the second one has much less product information than the first one. We found that according to degree of product information, there is a difference among perceived usefulness, privacy, attitude and actual behavior. And we also reveal weight difference between the two kinds of webpages. Finally, we indicated that variables have impact effect on both mutual relations and preceding relationships.

Centralized Machine Learning Versus Federated Averaging: A Comparison using MNIST Dataset

  • Peng, Sony;Yang, Yixuan;Mao, Makara;Park, Doo-Soon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.2
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    • pp.742-756
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    • 2022
  • A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

Efficient Hop-based Access Control for Private Social Networks (소셜 네트워크에서 프라이버시를 보호하는 효율적인 거리기반 접근제어)

  • Jung, Sang-Im;Kim, Dong-Min;Jeong, Ik-Rae
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.22 no.3
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    • pp.505-514
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    • 2012
  • Because people usually establish their online social network based on their offline relationship, the social networks (i.e., the graph of friendship relationships) are often used to share contents. Mobile devices let it easier in these days, but it also increases the privacy risk such as access control of shared data and relationship exposure to untrusted server. To control the access on encrypted data and protect relationship from the server, M. Atallah et al. proposed a hop-based scheme in 2009. Their scheme assumed a distributed environment such as p2p, and each user in it shares encrypted data on their social network. On the other hand, it is very inefficient to keep their relationship private, so we propose an improved scheme. In this paper, among encrypted contents and relationships, some authenticated users can only access the data in distributed way. For this, we adopt 'circular-secure symmetric encryption' first. Proposed scheme guarantees the improved security and efficiency compared to the previous work.