Concept Of Privacy Research Articles

Perceptions of older adults about the concept of privacy and in terms of video-based AAL technologies

Perceptions of older adults about the concept of privacy and in terms of video-based AAL technologies

A Q&A about Differential Privacy

This article is a Q&A on differential privacy (DP), a state-of-the-art and popular privacy concept. There are 11 questions, including “What is DP?”, the reasons for its popularity among privacy researchers, examples of real-world applications of DP, and open-source code and platforms on DP. For those who have heard about DP, but have not yet had a chance to read papers and publications on DP (either technical or non-technical) I hope this Q&A will provide something useful and insightful.

Investigation of Scientific Studies on Wearable Technologies in terms of Security and Privacy

This research aims to present the general situation of scientific publications in the WoS database dealing with wearable technologies in terms of security and privacy from a comprehensive and holistic perspective. A total of 71 publications were reached within the scope of the research by going through various screening processes. Document analysis method was used to collect the data, and content analysis method was used for the analysis. The results of the research show that there has been a steady increase in the number of publications on this subject since 2015. In particular, it has been observed that 86.8% of the publications have been published in the last five years. In addition, it has been revealed that the most publications on the subject are in the fields of "Computer Science", "Engineering", "Telecommunications" and "Science Technology". On the other hand, it has been seen that the concept of Security is used more than the concept of Privacy in the fields of Computer Science, Telecommunications and Engineering. In addition, when the keywords of the publications are mapped, it has been seen that the words "Wearable Technologies", "Security", "Privacy", "Internet of Things", "Authentication" and "Attack" are used more frequently.

Differential Privacy Protection for Support Vector Machines for Nonlinear Classification

Currently, private data leakage and nonlinear classification are two challenges encountered in big data mining. In particular, few studies focus on these issues in support vector machines (SVMs). In this paper, to effectively solve them, we propose a novel framework based on the concepts of differential privacy (DP) and kernel functions. This framework can allocate privacy budgets and add artificial noise to different SVM locations simultaneously, which makes the perturbation process freer and more delicate. In addition, under this framework, we propose three algorithms, DP SVMs that perturb the training data set, perturb the kernel function, and utilize mixed perturbation (DPSVM-TDP, DPSVM-KFP, and DPSVM-MP, respectively), all of which can realize accurate classification while ensuring that the users’ privacy is not violated. Moreover, we conduct privacy analysis on these algorithms and prove that they all satisfy ε , 0 − DP. Finally, we conduct experiments to evaluate the algorithms in terms of different aspects and compare them with the DPSVM with dual-variable perturbation (DVP) algorithm (DPSVM-DVP) to determine the optimal perturbation method. The results show that DPSVM-KFP can achieve the highest data utility and strictest privacy protection with the shortest running time.

Protecting The Privacy of Library Users

The purpose of this paper is to consider the best way of understanding the concept of informational privacy, including a discussion of what would be an appropriate theoretical framework and useful conceptual model; as well as how such a model can be used to investigate specific issues of library privacy.Two methodologies were used for the research: a literature review, and a thematic analysis of three pieces of data protection legislation. The research project is still in its relatively early stages, and the intention is to use several other methodologies to test the initial findings.Informational privacy is a derivative layer of other forms of privacy, and as such can only be properly understood in relation to each of the underlying privacy types. Where libraries rely for the delivery of their services on digital technologies provided by external vendors, they need to better understand whether and how those technologies impact upon each of the different types of privacy identified by (Koops et al. 2017).Using three pieces of data protection legislation to identify key themes does not give a complete picture of informational privacy; nor does it fully address the wider privacy implications. A detailed review of relevant case law on privacy from the European Court of Human Rights was not undertaken as part of this project. The choice of words and phrases appearing in data protection legislation and the subsequent grouping of them into broad themes is subjective.The observation that all library privacy scenarios have an informational privacy component alongside one or more privacy types has significant implications for information professionals intending to protect the privacy of their users; because, if correct, it means that simply complying with data protection laws does not fully address the protection of the underlying privacy types.

初探2019冠狀病毒病疫情下的私隱議題

LANGUAGE NOTE | Document text in Chinese; abstract also in English.
 現代科技日新月異，令我們生活更為方便，但亦帶來不少的道德問題。本文的主旨，正是從應用倫理學的角度來討論如何處理在2019冠狀病毒病持續全球大流行下，由此而來的私隱倫理問題。本文會特別聚焦在高等教育與社會預防及控制疾病政策這兩組例子當中涉及的私隱問題。根據後果評價的道德框架，本文會討論私隱與私隱權利的概念，還有不完整排序下最大化與最優化的分別。之後本文會討論控制論述與讀取論述對失去私隱的意義，然後會探討親密關係與私隱價值的互動，以此説明若要解決一些私隱的道德議題，討論親密關係的重要性是不可避免的。最後本文會詳細討論如何運用以上的分析，來處理兩組例子所涉及的私隱倫理問題。
 Alongside greater convenience, the rapid development of technology in the modern world has also brought about many ethical problems. This article examines privacy issues that emerged during the COVID-19 pandemic from the perspective of applied ethics. It focuses on two specific examples of privacy issues that emerged in higher education and social policy amid attempts to prevent and control the disease. Based on the moral framework of consequential evaluation, this article discusses the concepts of privacy and privacy rights and the difference between maximization and optimization in the context of an incomplete ranking of options. This article also discusses two ways that the loss of privacy has been understood: the control account and the access account. Another important discussion in the article is the place of privacy in the context of intimate relationships, and why the resolution of some issues concerning privacy requires a discussion of the concept of intimacy. Based on the above analysis, this article concludes with a discussion of how to evaluate the privacy issues in the two examples.

Re-thinking privacy in Australia in the wake of Dobbs v Jackson Women’s Health Organization

ABSTRACT In June 2022, the Supreme Court of the United States overturned its decision in Roe v Wade, 410 US 113 (1973), which had established a right to abortion founded on an implied constitutional right to privacy. The decision in Dobbs v Jackson Women’s Health Organization, 597 US (2022) has sparked fervent debate about women’s reproductive rights and access to healthcare in the United States. This article presents a decisional privacy perspective on Dobbs and considers its implications for privacy rights in Australia. The concept of decisional privacy protects an individual’s ability to make decisions which contribute to defining their identity, free from the unjustifiable interference of other individuals or the state. Drawing on examples of the violation of rights of LGBTQIA+ individuals, I argue that threats to decisional privacy are alive and well in Australia; yet a failure to conceptualise and articulate them as such undermines the value of privacy both to individuals and to society. The Dobbs decision offers a prime opportunity to re-think the meaning and value of privacy in Australian law and society, not only to enrich privacy law scholarship and jurisprudence but also to enable privacy to be more robustly protected as a human right.

E-Government and Privacy (Challenges and Solutions)

E-government, with all its advantages in improving government processes, reducing costs, reducing bureaucracy, creating an e-community and facilitating communication with citizens, also has its weaknesses. The most important concern about the development and growth of e-government is the violation of citizens' rights in cyberspace. One of the most important citizenship rights in cyberspace is the right to information privacy. Information privacy is a right. The right that individuals have to control their information against misplaced searches, eavesdropping, spying, misappropriation and misuse of personal information. In this article, the concept and models of e-government are examined and the concept of citizens' information privacy and its relationship with e-government is stated. For citizens' information privacy in e-government, the challenge of information privacy and e-government maturity, the challenge of information privacy and public interest, the protection of information privacy and freedom of information and the challenge of granting citizens the right to access information in e-government are the most important challenges of this study. have been identified

The notion of Privacy and Self with the Change of Social Media

Over the recent past, the world has witnessed increased uptake of social media and the use of internet. In particular, The world has witnessed tremendous growth in the number of people accessing social media through accessible mobile devices. In this foregoing, the use of social media has exposed millions of people to privacy infringement as voluminous personal information is shared via the social media and able to influence individuals' self-awareness along with self-image. The aim of this essay is to address the concepts of privacy and self consciousness, as well as the influence of self-orientated social media platforms such as Facebook, Twitter, and Tumblr on the processing of personal and private information and the relevance of this impact on self-presentation. The findings conclude the direct relationship between audience and media platforms, and thus can be used to suggest future research directions.

Adoption of mobile health services using the unified theory of acceptance and use of technology model: Self-efficacy and privacy concerns.

Mobile health (mHealth) services have been widely used in medical services and health management through mobile devices and multiple channels, such as smartphones, wearable equipment, healthcare applications (Apps), and medical platforms. However, the number of the users who are currently receiving the mHealth services is small. In China, more than 70% of internet users have never used mHealth services. Such imbalanced situation could be attributed to users’ traditional concept of medical treatment, psychological factors (such as low self-efficacy) and privacy concerns. The purpose of this study is to explore the direct and indirect effects of mHealth users’ self-efficacy and privacy concerns on their intention to adopt mHealth services, providing guidelines for mHealth service providers to enhance users’ intention of adoption. A questionnaire was designed by the research team and 386 valid responses were collected from domestic participants in China. Based on the unified theory of acceptance and use of technology (UTAUT) model, a research model integrated self-efficacy and privacy concerns was constructed to investigate their effects on users’ intention to adopt mobile mHealth services. The results show that self-efficacy could facilitate users’ intention to adopt mHealth services, and had a significantly positive effect on perceived ubiquity, effort expectancy, performance expectancy and subjective norm. This study verifies the direct and indirect effects of self-efficacy and privacy concerns on users’ intention to adopt mHealth services, providing a different perspective for studying mHealth adoption behavior. The findings could provide guidelines for mHealth service providers to improve their service quality and enhance users’ intention of adoption.

An Improved Approach of Iris Biometric Authentication Performance and Security with Cryptography and Error Correction Codes

One of the most challenging parts of integrating biometrics and cryptography is the intra variation in acquired identifiers between the same users. Due to noise in the environment or different devices, features of the iris may differ when it is acquired at different time periods. This research focuses on improving the performance of iris biometric authentication and encrypting the binary code generated from the acquired identifiers. The proposed biometric authentication system incorporates the concepts of non-repudiation and privacy. These concepts are critical to the success of a biometric authentication system. Iris was chosen as the biometric identifier due to its characteristics of high accuracy and the permanent presence throughout an individual’s lifetime. This study seeks to find a method of reducing the noise and error associated with the nature of dissimilarity acquired by each biometric acquisition. In our method, we used Reed Solomon error-correction codes to reduce dissimilarities and noise in iris data. The code is a block-based error correcting code that can be easily decoded and has excellent burst correction capabilities. Two different distance metric measurement functions were used to measure the accuracy of the iris pattern matching identification process, which are Hamming distance and weighted Euclidean distance. The experiments were conducted with the CASIA 1.0 iris database. The results showed that the False Acceptance Rate is 0%, the False Rejection Rate is 1.54%, and the Total Success Rate is 98.46%. The proposed approach appears to be more secure, as it is able to provide a low rate of false rejections and false acceptances.

Is AI recruiting (un)ethical? A human rights perspective on the use of AI for hiring

The use of artificial intelligence (AI) technologies in organizations’ recruiting and selection procedures has become commonplace in business practice; accordingly, research on AI recruiting has increased substantially in recent years. But, though various articles have highlighted the potential opportunities and ethical risks of AI recruiting, the topic has not been normatively assessed yet. We aim to fill this gap by providing an ethical analysis of AI recruiting from a human rights perspective. In doing so, we elaborate on human rights’ theoretical implications for corporate use of AI-driven hiring solutions. Therefore, we analyze whether AI hiring practices inherently conflict with the concepts of validity, autonomy, nondiscrimination, privacy, and transparency, which represent the main human rights relevant in this context. Concluding that these concepts are not at odds, we then use existing legal and ethical implications to determine organizations’ responsibility to enforce and realize human rights standards in the context of AI recruiting.

Privacy as a form of alienation: a critique of the liberal conception of privacy

The atrocities carried out by the Soviet Union have done a considerable harm to the Marxist social theory. Hence, it is being suggested that the revival of socialist politics is contingent upon its ability to engage with some of the central ideas associated with liberal theory. In this regard, privacy is projected as one of the central values about which Marxists need to seriously rethink. In this broad intellectual context, this paper aims to offer an unorthodox critique of the liberal conception of privacy through the Marxist conception of alienation. It asks: why are Marxists opposed to the liberal conception of privacy? Is privacy a form of alienation? How to conceptualise the interface between privacy, private property, and alienation under the capitalist mode of production? The paper argues that the liberal conception of privacy cannot be borrowed without significant modifications—as some scholars think—since it is based on an abstract and possessive conception of the individual, which is not only in accordance with the logic of capitalism but also breeds alienation.

3D Geo-Indistinguishability for Indoor Location-Based Services

Indoor location-based services (LBS) are widely used in large-scale indoor buildings, such as high-rise hospitals and multi-story shopping malls. At the same time, location privacy protection in such three-dimensional (3D) space has recently attracted considerable attention. Currently, most existing location privacy protection schemes focus on two-dimensional (2D) location protection and fail to prevent location inference attacks when the user’s location data include height dimension, i.e., 3D geolocation. Enlightened by the concept of differential privacy, in this paper we first study the impact factors of the degree of indistinguishability of 3D geolocations. Then, we quantify location privacy for LBS applications in the 3D space with geo-indistinguishability (3D-GI) rigorously and provably. We develop a mechanism of three-variates Laplacian to generate perturbed locations considering the locations’ X, Y, and Z-coordinates simultaneously, guaranteeing geo-indistinguishability. Furthermore, the discretization noise-adding mechanism is studied to satisfy geo-indistinguishability in the 3D space under the finite precision of hardware/devices. Considering the discretized mechanism can only satisfy geo-indistinguishability in finite 3D space and users visit the limited regions, we further study the truncation of the Laplacian mechanism to limit the generated perturbed locations within a specific region. Simulation results demonstrate that the proposed 3D-GI outperforms the benchmarks while guaranteeing privacy regardless of the adversary’s prior knowledge.

Conceptions of Privacy in the Digital Era: Perceptions of Slovak Citizens

In the digital era, citizens’ daily lives are taking place both in the physical and digital realms. At the same time, even the most mundane activities are increasingly affected by offline as well as online surveillance. The privacy paradigm suggests that there is a difference between the private and public spheres of life, and that with technological advancement the demarcation lines between these spheres have become blurred. As a consequence, citizens’ conceptions of privacy are becoming more fluid, nuanced, context-dependent, and socially determined. This gives rise to a need to reconceptualize what privacy means and how citizens think about its boundaries. To investigate citizens’ conceptions of privacy, we conducted six focus groups in Slovakia aimed at exploring people’s attitudes toward privacy and encompassing their experiences and rationalizations (including possible alterations) of behavior in a variety of everyday environments. The analysis suggests that privacy is a complex phenomenon that is understood as an interplay between different privacy norms guiding specific contexts and more general approaches to privacy. We identify four privacy environments (a controlled private space, a [voluntarily] shared private space, a transactional public space, and a non-controllable public space) and three privacy approaches (the reservations approach, the trade-off approach, and the death of privacy approach) whose interplay constitutes individuals’ conceptions of privacy. In addition, the acceptance of loss of privacy seems to depend on a perception of legitimacy, control over the mechanisms of surveillance that individuals encounter, and trust toward the data processor.

Surveillance and privacy as coevolving disruptions: reflections on “notice and choice”

The last two decades have seen a dramatic rise in the ways governments, private industry, and other interests can access, gather, analyze, and employ information about citizens. Given the unique roles of practitioners from both the public and private sectors in this policy ecosystem, we lay conceptual groundwork for coevolving technological, business, and policy disruptions. We focus on the “notice and choice” framework (which we consider a type of nudge) given changing conceptions of privacy in a world of evolving norms. Finally, we consider the difficult problem of clear guideposts for policy actors as they try to reconcile public demands for privacy with competing interests.

Social conceptions versus legal protections of privacy and information security in the context of encryption

ABSTRACT This article examines the disconnect between people’s social conceptions of privacy and information security in relation to encryption vis-à-vis the legal protections offered by law. It describes the social conceptions and expectations of participants based in New Zealand and contrasts these with the applicable laws and legal protections concerning privacy, information security and encryption. In light of incongruence between the social and the legal, the article recommends law and policy developments to better align and connect people’s social conceptions of privacy and information security with the legal protections provided by law. This includes having greater awareness of the relevance of civil and criminal procedure rights to privacy and information security in the context of encryption and providing stronger legal protections to the right against unreasonable search and seizure and the privilege against self-incrimination.

Strategies for Internet of Things data privacy and security using systematic review

The Internet of Things (IoT) now referend to as the Internet of Everything (IoE) has been in existence long before it was identified as a concept. It was introduced with the emergence of the Fourth Industrial Revolution and was aimed at improving people’s lives and economies across the globe by connecting physical items to the internet so they can be able to deliver specific services implicitly. The nature of IoT requires that all the systems ensure data privacy and security because much of data that is uploaded into and used by the system is personal and private. Thus, the aim of this research was to identify the tools and strategies that can be used for IoT data privacy and security while also providing a brief but intensive understanding of the concept of IoT and data privacy and security challenges faced by IoT systems. This qualitative research study utilised a pragmatic paradigm and data was collected and analysed using text-based secondary data sources and a PRISMA protocol through systematic review. A PRISMA flow diagram was utilised to assess the eligibility of the sources used for this research. The findings showed that hacking is a major challenge that affects IoT systems and that there are strategies that can be used to protect data such as authentication, encryption technology, and anonymisation amongst many. Additional findings found that the strategies have not yet been found effective, but standards have been set upon the results expected from them. The conclusion is that for the identified strategies to be proven effective, they must be implemented and tested in IoT systems, so further investigation can be conducted if they prove to be ineffective.

Probing archivists’ perceptions and practices in privacy

ABSTRACT Archivists participated in a survey to help provide insight around privacy and practice. The practitioners’ responses are bespeckled with varying levels of real-worklife experience with sensitive, private, and vulnerable archival information. The survey included some demographic questions as well as hypothetical scenarios, which prompted respondents to think about how they would respond in their professional capacities if these analogue, reformatted, or born-digital documents were under their stewardship, and invited respondents to share their own professional anecdotes of privacy practices. The survey and adjoining paper attempt to address two research questions, namely that around archivists’ decision-making in privacy issues in digitized collections, and if institutional policy informs practice. Responses indicate a variability in privacy practices specifically and in the concept of privacy broadly within the American organizations represented. Most archivists surveyed indicate they address privacy as a regular part of their practice, though we found very few had guiding practices or policies. Absence of targeted policy around privacy decision-making is prevalent in archives in the respondents’ institutions. Discussion around survey results is shared to serve as a springboard for informing policy-driven privacy practice, including recommendations for future research and some suggested resources.

Protection of Data Privacy in The Era of Artificial Intelligence in The Financial Sector in Indonesia

The concept of privacy has broad ramifications, and it is implemented in a number of disciplines, ranging from philosophy to computer science, political science and legal science. This paper covers the impact of artificial intelligence on privacy protection, especially in the finance sector. Privacy protection is associated with control over information about personal data, also known as private information. This research is a normative legal research of analytical nature, and it is conducted by studying and interpreting theoretical matters relating to the principles, conceptions, doctrines and legal norms pertaining to the problems. The results of this research show that the concept of privacy in the era of artificial intelligence in Indonesia is best achieved by combining comprehensive rules with self-regulation to serve as a balancing agent between laws and technology in order to control and fulfill the protection of personal data in the era of artificial intelligence.