• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.53-61
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• 2014

This research analyzed the relationship between CFIP and Intention to purchase under M-Commerce circumstances. First of all, CFIP had a negative influence on intention to purchase similar to E-Commerce. Secondly, we found privacy fundamentalist groups to react most sensitive to the degree of CFIP. Finally, Mobile experience did not have influence on the relationship between CFIP and Intention to purchase. This result is different from that of the E-Commerce Study. As such, it requires a more comprehensive research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.1043-1063
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• 2019

With delegating proxy to process data before outsourcing, data owners in restricted access could enjoy flexible and powerful cloud storage service for productivity, but still confront with data integrity breach. Identity-based data auditing as a critical technology, could address this security concern efficiently and eliminate complicated owners' public key certificates management issue. Recently, Yu et al. proposed an Identity-Based Public Auditing for Dynamic Outsourced Data with Proxy Processing (https://doi.org/10.3837/tiis.2017.10.019). It aims to offer identity-based, privacy-preserving and batch auditing for multiple owners' data on different clouds, while allowing proxy processing. In this article, we first demonstrate this scheme is insecure in the sense that malicious cloud could pass integrity auditing without original data. Additionally, clouds and owners are able to recover proxy's private key and thus impersonate it to forge tags for any data. Secondly, we propose an improved scheme with provable security in the random oracle model, to achieve desirable secure identity based privacy-preserving batch public auditing with proxy processing. Thirdly, based on theoretical analysis and performance simulation, our scheme shows better efficiency over existing identity-based auditing scheme with proxy processing on single owner and single cloud effort, which will benefit secure big data storage if extrapolating in real application.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.412-414
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• 2005

Because a sensor node must operate on a tiny battery, the goal to eliminate energy inefficiencies leads the current researchers excavating for new techniques to advocate. As sensor networks edge closer towards wide spread deployment, security issues become a central concern. So far much research has focused on making sensor networks feasible and useful, and has not concentrated much on security issues especially computationally inexpensive techniques. In this paper we introduce a simple scheme relying on one-way hash-functions that greatly enhances location privacy by changing traceable identifiers on every read getting by with only a single, unreliable message exchange. Thereby the scheme is safe from many threats like eavesdropping, message interception, spoofing, and replay attacks.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.197-209
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• 2011

The increasing popularity of graph data, such as social and online communities, has initiated a prolific research area in knowledge discovery and data mining. As more real-world graphs are released publicly, there is growing concern about privacy breaching for the entities involved. An adversary may reveal identities of individuals in a published graph, with the topological structure and/or basic graph properties as background knowledge. Many previous studies addressing such attacks as identity disclosure, however, concentrate on preserving privacy in simple graph data only. In this paper, we consider the identity disclosure problem in weighted graphs. The motivation is that, a weighted graph can introduce much more unique information than its simple version, which makes the disclosure easier. We first formalize a general anonymization model to deal with weight-based attacks. Then two concrete attacks are discussed based on weight properties of a graph, including the sum and the set of adjacent weights for each vertex. We also propose a complete solution for the weight anonymization problem to prevent a graph from both attacks. In addition, we also investigate the impact of the proposed methods on community detection, a very popular application in the graph mining field. Our approaches are efficient and practical, and have been validated by extensive experiments on both synthetic and real-world datasets.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.197-209
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• 2014

This study analyzed information privacy concerns and personal innovation influences effects of perceived usefulness, ease-of-use and satisfaction for a smartphone-based shopping mall, using technology acceptance model. For empirical analysis, the structural equation modeling analysis method was used. The results are as follows. First, information privacy concern is the usefulness of smartphone-based shopping mall has significantly negative, but did not affect the ease of use. Second, personal innovation is the usefulness and ease of use smartphone-based shopping mall have significant positive effect. Third, ease of use smartphone-based shopping mall is usefulness and satisfaction have significant positive influence. Finally, the usefulness of use of the shopping mall based smartphone significant satisfaction in positively influencing.

• Knowledge Management Research
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• v.16 no.3
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• pp.23-40
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• 2015

Despite much interest and investment in the Internet of Things (IoT) which expand the Internet to a ubiquitous network including objects in the physical world, there is growing concerns of privacy protections. Because the risk of privacy invasion is higher in IoT environments than ever before, privacy need to be a key issue in the diffusion of IoT. Considering that the privacy concern is a critical barrier for user to adopt information technologies, it is important to investigate users' privacy concerns related to IoT applications. From the triad perspective (i.e., risk on technology, risk on service provider, and trust on legislation), this study aims to examine users' privacy concerns in the context of activity trackers.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.143-153
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• 2013

Big data is expected to bring forth enormous public good as well as economic opportunity. However there is ongoing concern about privacy not only from public authorities but also from private enterprises. Big data is suspected to aggravate the existing privacy battle ground by introducing new types of privacy risks such as privacy risk of behavioral pattern. On the other hand, big data is asserted to become a new way to by-pass tradition behavioral tracking such as cookies, DPIs, finger printing${\cdots}$ and etc. For it is not based on a targeted person. This paper is to find out if big data could contribute to catching out behavioral patterns of consumers without threatening or damaging their privacy. The difference between traditional behavioral tracking and big data analysis from the perspective of privacy will be discerned.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.437-454
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• 2020

According to the privacy regulations of the health insurance portability and accountability act (HIPAA), patients' control over electronic health data is one of the major concern issues. Currently, remote access authorization is considered as the best solution to guarantee the patients' control over their health data. In this paper, a new biometric-based key management scheme is proposed to facilitate remote access authorization anytime and anywhere. First, patients and doctors can use their biometric information to verify the authenticity of communication partners through real-time video communication technology. Second, a safety channel is provided in delivering their access authorization and secret data between patient and doctor. In the designed scheme, the user's public key is authenticated by the corresponding biometric information without the help of public key infrastructure (PKI). Therefore, our proposed scheme does not have the costs of certificate storage, certificate delivery, and certificate revocation. In addition, the implementation time of our proposed system can be significantly reduced.

• Knowledge Management Research
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• v.25 no.2
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• pp.219-243
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• 2024

This study investigates the impact of privacy concerns, perceived utility, and awareness of the right to personal data self-determination on the effective use and expansion of MyData services, which are critical to the data economy. Integrating the value-based adoption model with privacy calculus theory, the research examines how perceived utility, privacy concerns, trust, and personal innovativeness influence perceived value, perceived privacy, and the intention to provide personal information. Data collected from an online survey of 442 MyData service users and prospective users were analyzed using PLS-SEM and Bootstrapping methods via SmartPLS 4. The results indicate that perceived utility positively affects the intention to provide personal information, while privacy concerns have a negative impact. Trust and personal innovativeness positively influence the intention to adopt MyData services, and the awareness of personal data self-determination rights moderates these intentions. The findings underscore the importance of developing beneficial services that mitigate users' privacy concerns and build trust for the successful implementation of MyData services. Additionally, the study highlights the need for education and awareness campaigns to enhance understanding of the right to personal data self-determination.

• Journal of Community Nutrition
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• v.8 no.1
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• pp.9-15
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• 2006

Health care is one of the most popular reasons for accessing the Internet. Of concern is the amount of information from disreputable sources available on the Internet. A review of websites offering nutrition consulting services suggests sites are controlled by both registered dietitians and non-dietitian professionals marketing themselves as nutrition consultants. The purpose of this study was to investigate structure and content of websites controlled by registered dietitians and nondietitians professionals marketing themselves as nutritionists or nutrition consultants. Internet search queries of 'dietitian', 'dietitian consultant', and 'nutrition consultant' were completed for website selection. Thirty websites controlled by registered dietitians and 10 websites controlled by nutrition consultants were reviewed using an 18-item website evaluation instrument developed for this study. Five evaluators were recruited from the dietetics program at the University of Kentucky. Overall, websites controlled by registered dietitians ranked higher than websites controlled by nutrition consultants in a majority of categories. Sites controlled by registered dietitians ranked statistically higher for the following categories: 'accuracy of information'(p<.0001), 'inclusion of professional resume of owner or primary manager' (p<.05), and 'explanation of the affiliation to externallinks'(p<.05). A majority of sites controlled by both dietitians and nutrition consultants achieved a poor ranking in regards to provision of a legal disclaimer and inclusion of a privacy policy. Prior studies suggest personal privacy is the most important concern for consumers accessing health information on the Internet. Findings from this project will benefit dietitians to assist in development of reputable nutrition related websites.