• Journal of the Korea Convergence Society
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• v.9 no.3
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• pp.231-240
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• 2018

Recently, personal information processing are becoming more important in the behavioral advertising based on online and mobile platform. The behavioral advertising analyzes and utilizes individual's search & purchase history, hobbies, and tendency based on the personal behavior information collected using the automatic collection device. Therefore, it collects and stores other types of personal information which did't defined in Privacy Act and can analyze personal behavior. This characteristics may cause disclosure of personal information and exposure to intrusion. In this paper, we investigate and analyze the privacy policy of the advertising agencies, and discussded the measures to be taken in collecting, storing and using personal information suitable for behavior information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1341-1368
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• 2024

The concept of privacy-preserving collaborative filtering (PPCF) has been gaining significant attention. Due to the fact that model-based recommendation methods with privacy are more efficient online, privacy-preserving memory-based scheme should be avoided in favor of model-based recommendation methods with privacy. Several studies in the current literature have examined ant colony clustering algorithms that are based on non-privacy collaborative filtering schemes. Nevertheless, the literature does not contain any studies that consider privacy in the context of ant colony clustering-based CF schema. This study employed the ant colony clustering model-based PPCF scheme. Attacks like shilling or profile injection could potentially be successful against privacy-preserving model-based collaborative filtering techniques. Afterwards, the scheme's robustness was assessed by conducting a shilling attack using six different attack models. We utilize masked data-based profile injection attacks against a privacy-preserving ant colony clustering-based prediction algorithm. Subsequently, we conduct extensive experiments utilizing authentic data to assess its robustness against profile injection attacks. In addition, we evaluate the resilience of the ant colony clustering model-based PPCF against shilling attacks by comparing it to established PPCF memory and model-based prediction techniques. The empirical findings indicate that push attack models exerted a substantial influence on the predictions, whereas nuke attack models demonstrated limited efficacy.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.39-51
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• 2019

As data grows rapidly, the provision of appropriate information needed by individuals has become an area of new services, and customized services which is enabling the analysis of optimal services through collecting, storing, and analyzing personal data are emerging in many fields. However, due to the characteristics of customized services based on various information collected by customers during the use of the service, the problem of privacy infringement is raised at the same time, and many studies are being actively conducted to solve this problem. This study seeks to explore how the customer's in-depth and customized services has an impact on their customers, which has not been derived from quantitative research using the grounded theory methodology. Through this, 84 concepts, 33 subcategories, 13 Categories and paradigm models were derived. In addition, 'Understanding and acceptance of online behavioral advertising (OBA)' was derived as a core category, and finally, acceptance types of OBA were classified into 'positive acceptance type', 'indifferent type', 'calculating type', and 'active resistance type' based on the key categories. This study divides the acceptance types of online behavioral advertising through the emotions and behaviors of the consumers throughout the procedure of online behavioral advertising experiences. In addition to the statistical and quantitative information currently used for providing behavioral advertising, it provides new criteria to reflect the refinement of behavioral advertising and personal tendencies or characteristics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.207-216
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• 2024

As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.167-175
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• 2005

Privacy enforcement has been one of the most important problems in IT area. Privacy protection can be achieved by enforcing privacy policies within an organization's online and offline data processing systems. Traditional security models are more or less inappropriate for enforcing basic privacy requirements, such as purpose binding. This paper proposes a new approach in which a privacy control model is derived from integration of an existing security model. To this, we use an extended role-based access control model for existing security mechanism, in which this model provides context-based access control by combining RBAC and domain-type enforcement. For implementation of privacy control model we use GRBAC(Generalized Role-Based Access Control), which is expressive enough to deal with privacy preference. And small hospital model is considered for application of this model.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.699-704
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• 2007

In this study, we examine why there exist different legal systems in electronic commerce or online financial trading. When a fraud online transaction occurs and the online customer disputes the transaction, the online customer takes responsibility for the proof of her/his argument in many European countries while in the U.S., the burden of proof lays on the firm. This paper analyzes how these two different legal systems exist and how these can be applied to electronic commerce law. In particular, this paper intends to find the optimal level of e-commerce firms' investment on security and analyzes how security investments can be related to firm's profits and consumer's welfare depending on IT infrastructure and social trust environment. More on, this paper can be contributed to provide guidelines for regulatory framework on ecommerce online transactions and discuss social welfare implications.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.59-71
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• 2014

This study applied customer perspective to find out ways how to protect customers' privacy by themselves. It does so by examining the factors which affect customer privacy protection behaviors. Based on the Privacy Act, this study developed the construct of Privacy Rights awareness and finds the law's effect on privacy awareness and behavioral change. The study finds that there exists a significant difference in privacy protection behavior according to privacy rights awareness. Independent variables are as follows: Five variables (Perceived vulnerability, Perceived severity, Perceived response effectiveness, Perceived barriers, Privacy Rights awareness) were tested as critical variables influencing Behavioral Intention in PMT model. Privacy awareness had a moderating effect on the relationship between perceived severity and privacy protection behavior. This study would contribute on theoretical expansion of Protection Motivation Theory and also provide practical implications for effective ways to promote behavioral changes.

• Asia pacific journal of information systems
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• v.32 no.1
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• pp.32-50
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• 2022

Technology acceptance is one of the most popular research areas. Rapid developments in technology are making human life more comfortable. However, still most of the rural area has been deprived of benefits of technological advancement. Seventy percent population of India resides in rural area. Leveraging the improved penetration of the internet; mobile friendly population in rural India has been increasingly shopping online in the last few years. e-Governance is one of the important vehicles to provide efficient services to the citizens by Governments. One major obstacle is acceptance of e-Governance platforms by the citizens. Considering the increasing trend of using e-Commerce in rural area, this paper attempts to investigate moderating effect of online shopping experience on intention to use e-Governance portals. We surveyed 365 villagers across Maharashtra: one of the leading states in India. The result confirmed online shopping experience moderates the relationship between: 'perceived security & privacy' and 'attitude'; 'perceived security & privacy' and 'intention to use'; 'Perceived usefulness' and 'attitude'; and, 'attitude' and 'intention to use'. In this study definition of moderating variable 'experience' is unique and different than most of the popular studies. We defined experience as: 'prior use of any application of technology similar to the target application of technology'. Whereas prior studies considered experience as prior experience with target application of the technology.

• Asia pacific journal of information systems
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• v.16 no.4
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• pp.49-70
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• 2006

In recent, Open markets are booming up rapidly. Open markets are one of the online marketplaces which mainly concentrated on spot transactions of commodities, and are differentiated from integrated internet shopping stores with market participants, trading rules and so on. This study investigated on factors affecting satisfaction with and preference on open markets by comparing open markets with integrated internet shopping stores, and aimed to figure out the reasons why open markets are growing up so rapidly and to forecast the future of open markets. To investigate the factors affecting buyers' satisfaction with and preference on internet shopping channel. I extracted several factors through literature reviews. The factors include the pros (cost saving and time saving), the cons (security concerns and privacy concerns), and decision making support suggested by Simon's research as well. Then, I constructed research model and related research hypotheses. To verify research hypotheses, I conducted field survey targeting on online buyers and analyzed research data using structural equation model. According to data analysis result, open markets have competitive advantages over integrated internet shopping stores with respect to cost saving, time saving, and decision making support. However, online buyers are still concerning privacy issues within open markets. In summary, buyers are considering that open markets are cheaper, faster, and more efficient internet shopping channel, compared with integrated internet shopping stores. However, open markets are required to dedicate to lessen buyers' privacy concerns to rebirth as more satisfying and preferable internet shopping channel and to prosper in the future.

• Korean journal of communication and information
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• v.80
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• pp.143-166
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• 2016

Recently, industrial values of big data as an important force of future society have been vastly paid attention. At the same time, more concerns about their private informations' disclosure online still echo around us, especially for them who have experiences of their personal information open online. This study aims to examine the questions; how people think about their personal information revealed online?; how much they have 'psychological reactance'?; what attitudes they have toward a certain governmental regulations on this? The findings of this study indicate that we should have more attentions to protect 'privacy' in the age of big-data and still need to make a lot of efforts to prepare a feasible regulation guide on this issue.