To Zoom or not to Zoom: Japanese and Ukrainian students’ attitudes towards online language learning

This paper reports on research that aimed to provide initial insight into how university students in two different countries, Japan and Ukraine, coped with greater use of videoconferencing software and whether this resulted in any issues surrounding their online privacy. To facilitate learning under the COVID-19 pandemic, instructors and learners had to speedily adapt to a ‘new normal’ of intense videoconferencing online learning. However, did this rapid implementation of online learning negatively impact students’ privacy? The findings presented in this reflective paper suggest that despite initial concerns, students who participated in the research exhibited low-level concerns regarding the impact of videoconferencing software on their online privacy. Although, students’ privacy concerns did grow when presented with long-term or permanent use of online learning as an integral part of a language learning structure.

AI Model for Predicting Legal Judgments to Improve Accuracy and Explainability of Online Privacy Invasion Cases

Since there are growing concerns regarding online privacy, firms may have the risk of being involved in various privacy infringement cases resulting in legal causations. If firms are aware of consequences from possible cases of invasion of online privacy, they can more actively prevent future online privacy infringements. Thus, this study attempts to predict the probability of judgment types caused by various invasions within US judicial cases that are related to online privacy invasions. Since legal judgment results are significantly influenced by societal factors and technological development, this study tries to identify a model that can accurately predict legal judgment with explainability. To archive the study objective, it compares the prediction performance by applying five types of classification algorithms (LDA, NNET, CART, SVM, and random forest) of machine learning. We also examined the relationship between privacy infringement factors and adjudications by applying network text analysis. The results indicate that firms could have a high possibility of both civil and criminal law responsibilities if they distributed malware or spyware, intentionally or non-intentionally, to collect unauthorized data. It addresses the needs of reflecting both quantitative and qualitative approach for establishing automatic legal systems for improving its accuracy based on the socio-technical perspective.

Improving Readability of Online Privacy Policies through DOOP: A Domain Ontology for Online Privacy

Privacy policies play an important part in informing users about their privacy concerns by operating as memorandums of understanding (MOUs) between them and online services providers. Research suggests that these policies are infrequently read because they are often lengthy, written in jargon, and incomplete, making them difficult for most users to understand. Users are more likely to read short excerpts of privacy policies if they pertain directly to their concern. In this paper, a novel approach and a proof-of-concept tool are proposed that reduces the amount of privacy policy text a user has to read. It does so using a domain ontology and natural language processing (NLP) to identify key areas of the policies that users should read to address their concerns and take appropriate action. Using the ontology to locate key parts of privacy policies, average reading times were substantially reduced from 29 to 32 min to 45 s.

Political Microtargeting and Online Privacy: A Theoretical Approach to Understanding Users’ Privacy Behaviors

Social media allow political parties to conduct political behavioral targeting in order to address and persuade specific groups of users and potential voters. This has been criticized: Most social media users do not know about these microtargeting strategies, and the majority of people who are aware of targeted political advertising say that it is not acceptable. This intrusion on personal privacy is viewed as problematic by users and activists alike. The overarching goal of this article is to elaborate on social media users’ privacy perceptions and potential regulating behaviors in the face of political microtargeting. This work is theoretical in nature. We first review theoretical and empirical research in the field of political microtargeting and online privacy. We then analyze how privacy is experienced by social media users during political microtargeting. Building on our theoretical analysis, we finally suggest clear-cut propositions for how political microtargeting can be researched while considering users’ privacy needs on the one hand and relevant political outcomes on the other.

The internet and consumer privacy - shopping basket or too hard basket

<p>The Internet has rapidly become the world’s most prevalent form of communication. It can be accessed twenty-four hours a day from virtually any location in the world from a myriad of technologically savvy devices. Internet users can keep up to date with world events, watch movies, listen to music, interact with government agencies, analyse business trends, undertake research and maintain contact with people anywhere. The Internet also provides the ability for users to shop ‘online’ with virtually any product or service supplier anywhere in the world. This has created concerns regarding the use of personal information obtained through the medium of the Internet. An individual’s right to privacy is a right enshrined in legislation and through tort law. With the uptake of technology and the burgeoning use of the Internet the subject of online privacy has become a complex issue for law and policy makers both in New Zealand and internationally. The aim of this paper is to look at the online shopper or consumer and how their information could be protected. This paper looks at the key areas of privacy legislation, the storage of data and the rise of new technologies including ‘cloud’ computing and suggests that the complexity of online privacy is such that a different approach to access and use of personal information of online shoppers may be required. The rate of technology change, the enormity of the data capture situation and the international accessibility of the Internet are all factors that create an almost impossible situation for ensuring consumer privacy so this paper proposes that the onus moves away from the law and policy makers and put into the hands of the users of the Internet.</p>

Efficiently Supporting Online Privacy-Preserving Data Publishing in a Distributed Computing Environment

There has recently been an increasing need for the collection and sharing of microdata containing information regarding an individual entity. Because microdata typically contain sensitive information on an individual, releasing it directly for public use may violate existing privacy requirements. Thus, extensive studies have been conducted on privacy-preserving data publishing (PPDP), which ensures that any microdata released satisfy the privacy policy requirements. Most existing privacy-preserving data publishing algorithms consider a scenario in which a data publisher, receiving a request for the release of data containing personal information, anonymizes the data prior to publishing—a process that is usually conducted offline. However, with the increasing demand for the sharing of data among various parties, it is more desirable to integrate the data anonymization functionality into existing systems that are capable of supporting online query processing. Thus, we developed a novel scheme that is able to efficiently anonymize the query results on the fly, and thus support efficient online privacy-preserving data publishing. In particular, given a user’s query, the proposed approach effectively estimates the generalization level of each quasi-identifier attribute, thereby achieving the k-anonymity property in the query result datasets based on the statistical information without applying k-anonymity on all actual datasets, which is a costly procedure. The experiment results show that, through the proposed method, significant gains in processing time can be achieved.

The Brave browser: a monetary opportunity for libraries in the cryptoverse

Purpose This paper aims to describe the benefits of the Brave web browser and its native cryptocurrency, the Basic Attention Token (BAT), for use by library patrons to preserve privacy and as a potential fundraising platform for libraries. Design/methodology/approach The Brave browser and BAT are introduced, an analysis of trends in adoption of these technologies is discussed and an argument for libraries to adopt/promote these technologies is presented. Findings Libraries could support the online privacy of their patrons if they encourage them to adopt the Brave browser, which is designed with privacy and security in mind. Libraries could also benefit from participating in the Brave Rewards program, which allows Brave users to donate BAT, a cryptotoken that they earn by viewing Brave ads, which can be traded for cash. Originality/value To the best of the author’s knowledge, this paper is the first to discuss the applications of the Brave browser in libraries and the potentials of cryptocurrency adoption by libraries.