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Information privacy

About: Information privacy is a research topic. Over the lifetime, 25412 publications have been published within this topic receiving 579611 citations. The topic is also known as: data privacy & data protection.


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Journal ArticleDOI
TL;DR: The results suggest that, in addition to using the default privacy settings, students have developed a number of strategies to address their privacy needs, and these strategies are used primarily to guard against social privacy threats.
Abstract: The privacy paradox describes people's willingness to disclose personal information on social network sites despite expressing high levels of concern. In this study, we employ the distinction between institutional and social privacy to examine this phenomenon. We investigate what strategies undergraduate students have developed, and their motivations for using specific strategies. We employed a mixed-methods approach that included 77 surveys and 21 in-depth interviews. The results suggest that, in addition to using the default privacy settings, students have developed a number of strategies to address their privacy needs. These strategies are used primarily to guard against social privacy threats and consist of excluding contact information, using the limited profile option, untagging and removing photographs, and limiting Friendship requests from strangers. Privacy strategies are geared toward managing the Facebook profile, which we argue functions as a front stage. This active profile management allows ...

260 citations

Journal ArticleDOI
TL;DR: A study of the existing laws regulating these aspects in the European Union and the United States, a review of the academic literature related to this topic, and a proposal of some recommendations for designers in order to create mobile health applications that satisfy the current security and privacy legislation are presented.
Abstract: In a world where the industry of mobile applications is continuously expanding and new health care apps and devices are created every day, it is important to take special care of the collection and treatment of users' personal health information. However, the appropriate methods to do this are not usually taken into account by apps designers and insecure applications are released. This paper presents a study of security and privacy in mHealth, focusing on three parts: a study of the existing laws regulating these aspects in the European Union and the United States, a review of the academic literature related to this topic, and a proposal of some recommendations for designers in order to create mobile health applications that satisfy the current security and privacy legislation. This paper will complement other standards and certifications about security and privacy and will suppose a quick guide for apps designers, developers and researchers.

260 citations

Journal ArticleDOI
TL;DR: This article presents a discussion on eight open challenges for data stream mining, which cover the full cycle of knowledge discovery and involve such problems as protecting data privacy, dealing with legacy systems, handling incomplete and delayed information, analysis of complex data, and evaluation of stream mining algorithms.
Abstract: Every day, huge volumes of sensory, transactional, and web data are continuously generated as streams, which need to be analyzed online as they arrive. Streaming data can be considered as one of the main sources of what is called big data. While predictive modeling for data streams and big data have received a lot of attention over the last decade, many research approaches are typically designed for well-behaved controlled problem settings, overlooking important challenges imposed by real-world applications. This article presents a discussion on eight open challenges for data stream mining. Our goal is to identify gaps between current research and meaningful applications, highlight open problems, and define new application-relevant research directions for data stream mining. The identified challenges cover the full cycle of knowledge discovery and involve such problems as: protecting data privacy, dealing with legacy systems, handling incomplete and delayed information, analysis of complex data, and evaluation of stream mining algorithms. The resulting analysis is illustrated by practical applications and provides general suggestions concerning lines of future research in data stream mining.

260 citations

Journal ArticleDOI
TL;DR: This paper uses two high-profile data breaches experienced by two U.S. companies, ChoicePoint and TJX, to illustrate the arguments for enhancing organizational level privacy programs based on ethical reasoning and makes recommendations for ways organizations can improve their privacy programs by incorporating moral responsibility.
Abstract: Protecting the privacy of personal information continues to pose significant challenges for organizations. Because consumers are vulnerable in their dealings with businesses due to a lack of information about and an inability to control the subsequent use of their personal information, we argue that organizations have a moral responsibility to these individuals to avoid causing harm and to take reasonable precautions toward that end. We further argue that firms can enhance their privacy programs by moving beyond merely complying with laws and other regulations and creating a culture of integrity that combines a concern for the law with an emphasis on managerial responsibility for the firm's organizational privacy behaviors. We use two high-profile data breaches experienced by two U.S. companies, ChoicePoint and TJX, to illustrate our arguments for enhancing organizational level privacy programs based on ethical reasoning. In doing so, this paper contributes to the dearth of prior organizational-level privacy research, which has largely overlooked ethical issues or the personal harms often caused by privacy violations. We conclude with recommendations for ways organizations can improve their privacy programs by incorporating moral responsibility.

258 citations

14 Apr 2008
TL;DR: This paper reports on the first iterative prototype, where presenting an audience-oriented view of profile information significantly improved the understanding of privacy settings.
Abstract: Users of online social networking communities are disclosing large amounts of personal information, putting themselves at a variety of risks. Our ongoing research investigates mechanisms for socially appropriate privacy management in online social networking communities. As a first step, we are examining the role of interface usability in current privacy settings. In this paper we report on our first iterative prototype, where presenting an audience-oriented view of profile information significantly improved the understanding of privacy settings.

257 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023562
20221,226
20211,535
20201,634
20191,255
20181,277