• Journal of Convergence for Information Technology
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• v.8 no.3
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• pp.79-84
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• 2018

Cloud services are readily available through a variety of media, attracting a lot of attention from users. However, there are various security damages that abuse the privacy of users who use cloud services, so there is not enough technology to prevent them. In this paper, we propose a protection model to safeguard user's privacy in a cloud environment so as not to illegally exploit user's privacy. The proposed model randomly manages the user's signature to strengthen the role of the middle manager and the cloud server. In the proposed model, the user's privacy information is provided illegally by the cloud server to the user through the security function and the user signature. Also, the signature of the user can be safely used by bundling the random number of the multiplication group and the one-way hash function into the hash chain to protect the user's privacy. As a result of the performance evaluation, the proposed model achieved an average improvement of data processing time of 24.5% compared to the existing model and the efficiency of the proposed model was improved by 13.7% than the existing model because the user's privacy information was group managed.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.3
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• pp.73-96
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• 2013

This study investigates how librarians view library user privacy. To this end, a four-part survey was conducted: respondents' opinions about the privacy of library users, the degree to which library records violate the users' privacy, the role libraries and librarians fulfill to ensure user privacy protection, and librarians' need for privacy education. Results showed that librarians were very aware of privacy issues, but they perceived that library users' privacy awareness was not high. In particular, they had little knowledge of what library records or which library tasks might have the potential to violate users' privacy. In addition, awareness efforts of librarians to ensure user privacy was very low. On the other hand, the need for library user privacy educational programs was shown to be very high, and the willingness to participate was also relatively high.

• The Journal of Information Systems
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• v.26 no.1
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• pp.93-123
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• 2017

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. In addition, this study, did empirical analysis of the path difference between groups by dividing Internet users into a group having experience in personal information spill and another group having no experience. 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.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.245-257
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• 2022

In the Internet of Things (IoT) era, the types of devices used by one user are becoming more diverse and the number of devices is also increasing. However, a forensic investigator is restricted to exploit or collect all the user's devices; there are legal issues (e.g., privacy, jurisdiction) and technical issues (e.g., computing resources, the increase in storage capacity). Therefore, in the digital forensics field, it has been a challenge to acquire information that remains on the devices that could not be collected, by analyzing the seized devices. In this study, we focus on the fact that multiple devices share data through account synchronization of the online platform. We propose a novel way of identifying the user's interest through analyzing the remnants of targeted advertising which is provided based on the visited websites or search terms of logged-in users. We introduce a detailed methodology to pick out the targeted advertising from cache data and infer the user's interest using deep learning. In this process, an improved learning model considering the unique characteristics of advertisement is implemented. The experimental result demonstrates that the proposed method can effectively identify the user interest even though only one device is examined.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.767-777
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• 2023

In modern society, user privacy is emerging as an important issue as closed-circuit television (CCTV) systems increase rapidly in various public and private spaces. If CCTV cameras monitor sensitive areas or personal spaces, they can infringe on personal privacy. Someone's behavior patterns, sensitive information, residence, etc. can be exposed, and if the image data collected from CCTV is not properly protected, there can be a risk of data leakage by hackers or illegal accessors. This paper presents an innovative approach to "machine learning based reversible chaotic masking method for user privacy protection in CCTV environment." The proposed method was developed to protect an individual's identity within CCTV images while maintaining the usefulness of the data for surveillance and analysis purposes. This method utilizes a two-step process for user privacy. First, machine learning models are trained to accurately detect and locate human subjects within the CCTV frame. This model is designed to identify individuals accurately and robustly by leveraging state-of-the-art object detection techniques. When an individual is detected, reversible chaos masking technology is applied. This masking technique uses chaos maps to create complex patterns to hide individual facial features and identifiable characteristics. Above all, the generated mask can be reversibly applied and removed, allowing authorized users to access the original unmasking image.

• Journal of Information Processing Systems
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• v.6 no.2
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• pp.185-196
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• 2010

This paper proposes a personal information protection model that allows a user to regulate his or her own personal information and privacy protection policies to receive services provided by a service provider without having to reveal personal information in a way that the user is opposed to. When the user needs to receive a service that requires personal information, the user will only reveal personal information that they find acceptable and for uses that they agree with. Users receive desired services from the service provider only when there is agreement between the user's and the service provider's security policies. Moreover, the proposed model utilizes a mobile agent that is transmitted from the user's personal space, providing the user with complete control over their privacy protection. In addition, the mobile agent is itself a self-destructing program that eliminates the possibility of personal information being leaked. The mobile agent described in this paper allows users to truly control access to their personal information.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.189-200
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• 2011

With rapid development and contribution of IT technology IT fushion healthcare service which is a form of future care has been changed a lot. Specially, as IT technology unites with healthcare, because delicate personal medical information is exposed and user's privacy is invaded, we need preperation. In this paper, u-healthcare service model which can manage patient's ID information as user's condition and access level is proposed to protect user's privacy. The proposed model is distinguished by identification, certification of hospital, access control of medical record, and diagnosis of patient to utilize it efficiently in real life. Also, it prevents leak of medical record and invasion of privacy by others by adapting user's ID as divided by user's security level and authority to protect privacy on user's information shared by hospitals.

• Annual Conference of KIPS
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• 2013.05a
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• pp.621-624
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• 2013

Mobile Cloud Computing is today's emerging technology. Customers enjoy the services and application from this combination of mobile technology and cloud computing. Beside all these benefits it also increases the concerns regarding privacy of users, while interacting with this new paradigm One of the services is Location based services, but to get their required services user has to give his/her current location to the LBS provider that is violation of location privacy of mobile client. Many approaches are in literature for preserve location privacy but some has computation restriction and some suffer from lack of privacy. In this paper we proposed a novel idea that not only efficient in its protocol but also completely preserves the user's privacy. The result shows that by sharing just service name and a large enough geographic area (e.g. a city) user gets required information from the server by doing little client side processing We perform experiments at client side by developing and testing an android based mobile client application to support our argument.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.618-627
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• 2014

Nowadays mobile users are using a popular service called Location-Based Services (LBS). LBS is very helpful for a mobile user in finding various Point of Interests (POIs) in their vicinity. To get these services, users must provide their personal information, such as user identity or current location, which severely risks the location privacy of the user. Many researchers are developing schemes that enable a user to use these LBS services anonymously, but these approaches have some limitations (i.e., either the privacy prevention mechanism is weak or the cost of the solution is too much). As such, we are presenting a robust scheme for mobile users that allows them to use LBS anonymously. Our scheme involves a client side application that interacts with an untrusted LBS server to find the nearest POI for a service required by a user. The scheme is not only efficient in its approach, but is also very practical with respect to the computations that are done on a client's resource constrained device. With our scheme, not only can a client anonymously use LBS without any use of a trusted third party, but also a server's database is completely secure from the client. We performed experiments by developing and testing an Android-based client side smartphone application to support our argument.

• 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.