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

• International Journal of Computer Science & Network Security
• /
• v.24 no.6
• /
• pp.99-108
• /
• 2024

The Internet of Things (IoT) is a novel concept that allows a large number of objects to be connected to the Internet while also allowing them to be controlled remotely. The Internet of Things is extensive and has become an almost inseparable part of our daily lives. Users' personal data is frequently obtained by these linked gadgets and stored online. In recent years, the security of acquired data has become a major concern. As devices grow more linked, privacy and security concerns grow more pressing, and they must be addressed as soon as possible. IoT implementations and devices are particularly vulnerable to attacks that might adversely affect customer security and privacy, which might have an impact on their practical utility. The goal of this study is to bring attention to the security and privacy concerns that exist in IoT systems. To that purpose, the paper examines security challenges at each level of the IoT protocol stack, identifies underlying impediments and critical security requirements, and provides a rapid overview of available security solutions for securing IoT in a layered environment.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.5
• /
• pp.294-301
• /
• 2017

Recently, online social networks have become one of the most representative Internet services and are being used increasingly, which allows people to share information and interact with other people. On the other hand, as the use of OSN is increased, there has been an increased incidence where illegally accessed personal information is used wrongfully. Accordingly, privacy has become a key concern by the users. Regarding the construct of information privacy concerns (IPC), this study explored the antecedents of IPC at the individual personal level - risk appraisal and perceived behavioral control - based on Protection Motivation Theory. Hence, the current paper investigated the moderating effect of gender in the relationship between individual characteristics and IPC. The hypothesized research model was examined with 233 questionnaires of OSN users. The results showed that the positive effects of risk appraisal and the negative effects of perceived behavioral control on IPC are supported. In addition, the moderate effects of gender between risk appraisal and IPC is only supported.

• Knowledge Management Research
• /
• v.21 no.4
• /
• pp.211-225
• /
• 2020

We investigate factors affecting chatbot use intention of online shopping mall users. We identify theoretical foundations from the literature and postulate that accuracy, personalization level, intelligence, intimacy, social presence, and piracy concern should affect intention to use more or negative intention to use. Based on 300 responses from online shopping mall chatbot users in Korea, we run the statistical analysis to assure the reliability and validity of the measurements. From the multiple regression analysis, we find that personalization level, intelligence, social presence, and privacy concerns significantly affect intention to use more. In contrast, we find that accuracy and privacy concerns significantly affect negative intention to use. This work will present pragmatic implications upon the design and management of chatbot in order to not only incent customers to use more but reduce factors that may cause negative use intention. Among functional factors, personalization and intelligence increases the intention to use more while accuracy decreases negative intention to use. Among emotional factors such as intimacy and social presence, we find that only social presence significantly increases intention to use more. Privacy concerns is found to decrease intention to use and increase negative intention to use.

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

• Informatization Policy
• /
• v.30 no.2
• /
• pp.22-45
• /
• 2023

In research on the use of AI-based voice assistant services, problems related to the user's trust and privacy protection arising from the experience of service use are constantly being raised. The purpose of this study was to investigate empirically the effects of individual trust in AI and online privacy concerns on the continued use of AI-based voice assistants, specifically the impact of their interaction. In this study, question items were constructed based on previous studies, with an online survey conducted among 405 respondents. The effect of the user's trust in AI and privacy concerns on the adoption and continuous use intention of AI-based voice assistant services was analyzed using the Heckman selection model. As the main findings of the study, first, AI-based voice assistant service usage behavior was positively influenced by factors that promote technology acceptance, such as perceived usefulness, perceived ease of use, and social influence. Second, trust in AI had no statistically significant effect on AI-based voice assistant service usage behavior but had a positive effect on continuous use intention. Third, the privacy concern level was confirmed to have the effect of suppressing continuous use intention through interaction with trust in AI. These research results suggest the need to strengthen user experience through user opinion collection and action to improve trust in technology and alleviate users' concerns about privacy as governance for realizing digital government. When introducing artificial intelligence-based policy services, it is necessary to disclose transparently the scope of application of artificial intelligence technology through a public deliberation process, and the development of a system that can track and evaluate privacy issues ex-post and an algorithm that considers privacy protection is required.

• Information Systems Review
• /
• v.16 no.3
• /
• pp.135-160
• /
• 2014

Most Social Network Service (SNS) provide online chat, video and file sharing, blogging and others. Because of this advantage, people depend on SNS to communicate with others. However, recently SNS encourage people to reveal too much information broadly so SNS users are concerned about privacy invasion and data spill. They also feel fatigue in process of touching people they don't know while using SNSs. That is the reason why they attempt to switch from opened SNS to Closed SNS. Therefore, the purpose of this study is to empirically investigate and analyze the effect of the factors on the SNS users' switching behavior when using SNS. To accomplish this purpose, this research adopted "Push-Pull-Mooring (PPM)" framework. The PPM is proposed by population geologist, who used it to explain the incentives of demographic migration. Following PPM model, this research empirically examines the three categories of antecedents for SNS switching intention toward closed SNS: push (i.e., weak connection, privacy concern, relative complexity), pull (i.e., enjoyment, belongingness, peer influence), mooring (i.e., SNS fatigue, user resistance) factors. The survey was conducted for 285 users on SNS communities in Korea. The results of this study are as follows; First, wear connection and privacy concern are significantly related to SNS switching intention. Second, enjoyment and belongingness are significantly related to SNS switching intention. Finally, the results show that SNS fatigue has a moderating effect on the links between push factors and SNS switching Intention. Also, user resistance has a moderating effect on the links between pull factors and SNS switching Intention. These findings contribute to the SNS literature both theoretically and practically.

• Information Systems Review
• /
• v.20 no.3
• /
• pp.33-49
• /
• 2018

Since there are growing concerns regarding personal information, users have perceived the importance of it. It makes users try to manage and control personal information by their own intentions. Therefore, we assume users now have begun to perceive psychological ownership on personal information. A main objective of this study is to identitythe relationship between accountability, self-identity, self-efficacy and sense of belongingness and psychological ownership on personal information. We conduct an online-basedsurvey and establish a structural equation model for testing hypothesis. The results show that users' accountability, self-identity and sense of belongingness positively influence to psychological ownership on personal information. Additionally, users' perceived psychological ownership on personal information increase their concern for information privacy. This study suggests a new concept as 'perceived psychological ownership on personal information' to explain for intentions of their psychological possessions toward personal information. The findings of this study can provide a way for how firms have to require clients' personal information with increasing their satisfactions.

• The Journal of the Korea Contents Association
• /
• v.14 no.9
• /
• pp.188-202
• /
• 2014

This major purpose of this study is to examine factors influencing the attitude toward News Feed advertising in Facebook. For this purpose, this study posited seven determinants including informativeness, entertainment, irritation, trust, individualization, incentive and privacy concern, which can have influences on the attitude toward News Feed Advertising. and this research tests the relationships between these seven determinants and the attitude toward News Feed Advertising. An online survey was administrated to collect data and hierarchical regression analyses were employed for data analysis. The results showed that infortainment as a new combined factor of informativeness and entertainment, trust, individualization have significantly positive influences on the attitude toward News Feed advertising in Facebook. It was also shown that the moderating effect of involvement on the relationship between irritation and the attitude. The results in this study implied that it is needed to reinforce the attributes of advertising including infortainment, trust and individualization to boost the effects of News Feed advertising in Facebook on consumers.