Browser Plug-in Research Articles

GDPR Transparency as a Research Method

Data-driven research is rapidly becoming mainstream across different disciplines in academia and in investigative journalism. One of the key challenges researchers often struggle with is how to obtain good data. Whether one investigates political micro-targeting, discriminatory insurance practices, or physical exercise patterns across demographics, all require high-quality data. Obtaining the necessary data often depends on the goodwill of the entity in control of that data, frequently a private entity carefully guarding its data-assets. Researchers have tried to find ways round this through a range of technical tools (e.g. browser plugins, data scraping), with varying degrees of success. This paper purports to add an important legal tool to the catalogue of data-driven research methods: i.e. GDPR transparency measures, and data subject rights in particular. The reinforced data subject rights in the General Data Protection Regulation (GDPR) have been lauded (and denounced) for their apparent potency. Especially the rights of access, portability and ‘explanation’ are said to ensure important values such as autonomy, accountability and fairness. To make true on this promise, these rights can (should?) be used as a methodological tool for investigative research. Not just to scrutinize the data practices of those holding the data (e.g. uncovering discrimination), but also to enable broader research objectives (e.g. informing health policies). Indeed, these rights offer a legal hook to effectively crowdsource data-driven research. Against this backdrop, the paper will describe the merits, challenges, limitations and best practices of using data subject rights as a research method. It will do so by building on past experiences of some first initiatives in the EU and assessing how the growing number of ‘download my data’ tools are useful/less. After an introductory section setting out some of the issues currently faced in data-driven research, the paper will explain how they might (not) be tackled by some of the key features of using GDPR transparency measures as a research method. The following section (4) is perhaps the core of the paper, describing the legal and practical operationalisation of these novel research methods, as well as the requirements for making them meaningful. The final section then takes a step back, positioning GDPR transparency measures within their broader (research methods and economic-technical) surroundings.

Computational observation

Abstract A lot of modern media use is guided by algorithmic curation, a phenomenon that is in desperate need of empirical observation, but for which adequate methodological tools are largely missing. To fill this gap, computational observation offers a novel approach—the unobtrusive and automated collection of information encountered within algorithmically curated media environments by means of a browser plug-in. In contrast to prior methodological approaches, browser plug-ins allow for reliable capture and repetitive analysis of both content and context at the point of the actual user encounter. After discussing the technological, ethical, and practical considerations relevant to this automated solution, we present our open-source browser plug-in as an element in an adequate multi-method design, along with potential links to panel surveys and content analysis. Ultimately, we present a proof-of-concept study in the realm of news exposure on Facebook; we successfully deployed the plug-in to Chrome and Firefox, and we combined the computational observation with a two-wave panel survey. Although this study suffered from severe recruitment difficulties, the results indicate that the methodological setup is reliable and ready to implement for data collection within a variety of studies on media use and media effects.

Building and Studying a Password Store that Perfectly Hides Passwords from Itself

We introduce a novel approach to password management, called SPHINX, which remains secure even when the password manager itself has been compromised. In SPHINX, the information stored on the device is theoretically independent of the user's master password. Moreover, an attacker with full control of the device, even at the time the user interacts with it, learns nothing about the master password - the password is not entered into the device in plaintext form or in any other way that may leak information on it. Unlike existing managers, SPHINX produces strictly high-entropy passwords and makes it compulsory for the users to register these passwords with the web services, which defeats online guessing attacks and offline dictionary attack upon service compromise. We present the design, implementation and performance evaluation of SPHINX, offering prototype browser plugins, smartphone apps and transparent device-client communication. We further provide a comparative analytical evaluation of SPHINX with other password managers based on a formal framework consisting of security, usability, and deployability metrics.

Susceptibility to Spear-Phishing Emails: Effects of Internet User Demographics and Email Content.

Phishing is fundamental to cyber attacks. This research determined the effect of Internet user age and email content such as weapons of influence (persuasive techniques that attackers can use to lure individuals to fall for an attack) and life domains (a specific topic or aspect of an individual's life that attackers can focus an emails on) on spear-phishing (targeted phishing) susceptibility. One-hundred young and 58 older users received, without their knowledge, daily simulated phishing emails over 21 days. A browser plugin recorded their clicking on links in the emails as an indicator of their susceptibility. Forty-three percent of users fell for the simulated phishing emails, with older women showing the highest susceptibility. While susceptibility in young users declined across the study, susceptibility in older users remained stable. The relative effectiveness of the attacks differed by weapons of influence and life domains with age-group variability. In addition, older compared to young users reported lower susceptibility awareness. These findings support effects of Internet user demographics and email content on susceptibility to phishing and emphasize the need for personalization of the next generation of security solutions.

Analysis of server-side and client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and geoportal

The last decade has seen a rapid evolution of processing, analysis and visualization of freely available geographic data using Open Source Web-GIS. In the beginning, Web-based Geographic Information Systems employed a thick-client approach which required installation of platform-specific browser plugins. Later on, research focus shifted to platform-independent thin client solutions in which data processing and analysis was performed by the server machine. More recently, however, the rapid development of computer hardware as well as software technologies such has HTML5 has enabled the creation of platform-independent thick clients which offer advanced GIS functionalities such as geoprocessing. This article aims to analyse the current state of Open Source technologies and publicly available geographic data sources in the context of creating cost-effective Web-GIS applications for integration and processing of spatial data. For this purpose the article discusses the availability and potential of Web-GIS architectures, software libraries and data sources. The analysis of freely available data sources includes a discussion of the quality and accuracy of crowd-sourced as well as public sector data, while the investigation of software libraries and architectures involves a comparison of server-side and client-side data processing performance under a set of real-world scenarios. The article concludes with a discussion of the choice of cost-effective Web-GIS architectures, software libraries and data sources in the context of the institution and environment of system deployment.

Access to Top-Cited Emergency Care Articles (Published Between 2012 and 2016) Without Subscription.

IntroductionUnrestricted access to journal publications speeds research progress, productivity, and knowledge translation, which in turn develops and promotes the efficient dissemination of content. We describe access to the 500 most-cited emergency medicine (EM) articles (published between 2012 and 2016) in terms of publisher-based access (open access or subscription), alternate access routes (self-archived or author provided), and relative cost of access.MethodsWe used the Scopus database to identify the 500 most-cited EM articles published between 2012 and 2016. Access status was collected from the journal publisher. For studies not available via open access, we searched on Google, Google Scholar, Researchgate, Academia.edu, and the Unpaywall and Open Access Button browser plugins to locate self-archived copies. We contacted corresponding authors of the remaining inaccessible studies for a copy of each of their articles. We collected article processing and access costs from the journal publishers, and then calculated relative cost differences using the World Bank purchasing power parity index for the United States (U.S.), Germany, Turkey, China, Brazil, South Africa, and Australia. This allows costs to be understood relative to the economic context of the countries from which they originated.ResultsWe identified 500 articles for inclusion in the study. Of these, 167 (33%) were published in an open access format. Of the remaining 333 (67%), 204 (61%) were available elsewhere on the internet, 18 (4%) were provided by the authors, and 111 (22%) were accessible by subscription only. The mean article processing and access charges were $2,518.62 and $44.78, respectively. These costs were 2.24, 1.75, 2.28 and 1.56 times more expensive for South African, Chinese, Turkish, and Brazilian authors, respectively, than for U.S. authors (p<0.001 all).ConclusionDespite the advantage of open access publication for knowledge translation, social responsibility, and increased citation, one in five of the 500 EM articles were accessible only via subscription. Access for scientists from upper-middle income countries was significantly hampered by cost. It is important to acknowledge the value this has for authors from low- and middle-income countries. Authors should also consider the citation advantage afforded by open access publishing when deciding where to publish.

The Role of the User's Browsing and Query History for Improving MPC-generated Query Suggestions

In this paper we use the user's recent web browsing history in order to provide better query suggestions in an information retrieval system. We have built a Chrome browser plugin that collects each web page visited by a user and submits it to our query suggestion server for indexing, thus building a personal history profile for each user. We then analyze if future queries submitted by a user to the search engine can be predicted from web pages visited by that user in the past (i.e. his recent browsing history) or from queries submitted by that user in the past (i.e. his recent query history). The contribution of this paper is a method of using this personal history profile for reordering the query suggestions offered by Google when the user searches information on Google, moving query suggestions more relevant to the user's information need to the front positions in the Google provided query suggestions list. We have collected browsing history log data for over 4 months from several users who installed our Chrome plugin on their local computers and then we performed an offline evaluation test that shows that our personalized query suggestion system improves the MRR (i.e. Mean Reciprocal Rank) score of Google query suggestions by approximately 0.04 (i.e. improves Google's MRR score by 12 percents).

SugarSketcher: Quick and Intuitive Online Glycan Drawing.

SugarSketcher is an intuitive and fast JavaScript interface module for online drawing of glycan structures in the popular Symbol Nomenclature for Glycans (SNFG) notation and exporting them to various commonly used formats encoding carbohydrate sequences (e.g., GlycoCT) or quality images (e.g., svg). It does not require a backend server or any specific browser plugins and can be integrated in any web glycoinformatics project. SugarSketcher allows drawing glycans both for glycobiologists and non-expert users. The “quick mode” allows a newcomer to build up a glycan structure having only a limited knowledge in carbohydrate chemistry. The “normal mode” integrates advanced options which enable glycobiologists to tailor complex carbohydrate structures. The source code is freely available on GitHub and glycoinformaticians are encouraged to participate in the development process while users are invited to test a prototype available on the ExPASY web-site and send feedback.

Fine-Grained Control over Tracking to Support the Ad-Based Web Economy

The intrusiveness of Web tracking and the increasing invasiveness of digital advertising have raised serious concerns regarding user privacy and Web usability, leading a substantial chunk of the populace to adopt ad-blocking technologies in recent years. The problem with these technologies, however, is that they are extremely limited and radical in their approach, and they completely disregard the underlying economic model of the Web, in which users get content free in return for allowing advertisers to show them ads. Nowadays, with around 200 million people regularly using such tools, said economic model is in danger. In this article, we investigate an Internet technology that targets users who are not, in general, against advertising, accept the trade-off that comes with the “free” content, but—for privacy concerns—they wish to exert fine-grained control over tracking. Our working assumption is that some categories of web pages (e.g., related to health or religion) are more privacy-sensitive to users than others (e.g., about education or science). Capitalizing on this, we propose a technology that allows users to specify the categories of web pages that are privacy-sensitive to them and block the trackers present on such web pages only. As tracking is prevented by blocking network connections of third-party domains, we avoid not only tracking but also third-party ads. Since users continue receiving ads on those web pages that belong to non-sensitive categories, our approach may provide a better point of operation within the trade-off between user privacy and the Web economy. To test the appropriateness and feasibility of our solution, we implemented it as a Web-browser plug-in, which is currently available for Google Chrome and Mozilla Firefox. Experimental results from the collected data of 746 users during one year show that only 16.25% of ads are blocked by our tool, which seems to indicate that the economic impact of the ad-blocking exerted by privacy-sensitive users could be significantly reduced.

An Evaluation of HTML5 and WebGL for Medical Imaging Applications.

Despite the fact that a large number of web applications are used in the medical community, there are still certain technological challenges that need to be addressed, for example, browser plug-ins and efficient 3D visualization. These problems make it necessary for a specific browser plug-in to be preinstalled on the client side when launching applications. Otherwise, the applications fail to run due to the lack of the required software. This paper presents the latest techniques in hypertext markup language 5 (HTML5) and web graphics library (WebGL) for solving these problems and an evaluation of the suitability of the combination of HTML5 and WebGL for the development of web-based medical imaging applications. In this study, a comprehensive medical imaging application was developed using HTML5 and WebGL. This application connects to the medical image server, runs on a standard personal computer (PC), and is easily accessible via a standard web browser. The several functions required for radiological interpretation were implemented, for example, navigation, magnification, windowing, and fly-through. The HTML5-based medical imaging application was tested on major browsers and different operating systems over a local area network (LAN) and a wide area network (WAN). The experimental results revealed that this application successfully performed two-dimensional (2D) and three-dimensional (3D) functions on different PCs over the LAN and WAN. Moreover, it demonstrated an excellent performance for remote access users, especially over a short time period for 3D visualization and a real-time fly-through navigation. The results of the study demonstrate that HTML5 and WebGL combination is suitable for the development of medical imaging applications. Moreover, the advantages and limitations of these technologies are discussed in this paper.

SMILK, trait d’union entre langue naturelle et données sur le web

As part of the SMILK Joint Lab, we studied the use of Natural Language Processing to: (1) enrich knowledge bases and link data on the web, and conversely (2) use this linked data to contribute to the improvement of text analysis and the annotation of textual content, and to support knowledge extraction. The evaluation focused on brand-related information retrieval in the field of cosmetics. This article describes each step of our approach: the creation of ProVoc, an ontology to describe products and brands; the automatic population of a knowledge base mainly based on ProVoc from heterogeneous textual resources; and the evaluation of an application which that takes the form of a browser plugin providing additional knowledge to users browsing the web.

All That Glitters Is Gold — An Attack Scheme on Gold Questions in Crowdsourcing

One of the most popular quality assurance mechanisms in paid micro-task crowdsourcing is based on gold questions: the use of a small set of tasks of which the requester knows the correct answer and, thus, is able to directly assess crowd work quality. In this paper, we show that such mechanism is prone to an attack carried out by a group of colluding crowd workers that is easy to implement and deploy: the inherent size limit of the gold set can be exploited by building an inferential system to detect which parts of the job are more likely to be gold questions. The described attack is robust to various forms of randomisation and programmatic generation of gold questions. We present the architecture of the proposed system, composed of a browser plug-in and an external server used to share information, and briefly introduce its potential evolution to a decentralised implementation. We implement and experimentally validate the gold detection system, using real-world data from a popular crowdsourcing platform. Finally, we discuss the economic and sociological implications of this kind of attack.

The Innovative Use of Mathematica to Teach Biodiversity

We investigated using Mathematica to create an interactive exercise that allows students to explore biological concepts. Exporting these active learning experiences to the Wolfram Computable Document Format (CDF) lets students enter data and modify parameters with only a browser plug-in and without needing to know how to use Mathematica. This exercise enhances student understanding by allowing them to focus on the biological concepts and visualize the data and calculations without the tedium of hand computation. In this article, we will highlight an interactive version of a biodiversity laboratory that explores Simpson's Diversity Index. Students are walked through sample calculations with a small data set, and then analyze a larger data set, which is presented as a set of interactive graphs and automatic calculations so that they can explore the data to answer questions. For our non-major audience, this laboratory leads to a more sophisticated discussion without getting stuck on the calculations. We will present the exercise and assessment results.

Automated analysis of freeware installers promoted by download portals

We present an analysis system for studying Windows application installers. The analysis system is fully automated from installer download to execution and data collection. The system emulates the behavior of a lazy user who wants to finish the installation dialogs with the default options and with as few clicks as possible. The UI automation makes use of image recognition techniques and heuristics. During the installation, the system collects data about the system modification and network access. The analysis system is scalable and can run on bare-metal hosts as well as in a data center. We use the system to analyze 792 freeware application installers obtained from popular download portals. In particular, we measure how many of them drop potentially unwanted programs (PUP) such as browser plugins or make other unwanted system modifications. We discover that most installers that download executable files over the network are vulnerable to man-in-the-middle attacks. We also find, that while popular download portals are not used for blatant malware distribution, nearly 10% of the analyzed installers come with a third-party browser or a browser extension.

Extend an Algorithm of Auto-converting Kurdish Written Scripts in Websites: from Latin Characters to Kurdish/Arabic Characters and Vice Versa

Nowadays, most Kurdish websites, especially news websites are required both written scripts (Latin and Kurdish/Arabic) for their users, for example, Rudaw, WAAR, NRT, etc. Therefore, designing two websites for each written script require effort, time and cost. There are web-based applications available for users not web developers to converting script manually, regardless of accuracy (misspellings), in this case, users have to input script to input box like pelk , KAL (Kurdish Academic of language) website, etc.(Jemal Nebez, 2015)(pellk, 2010). This research develops an algorithm which can auto-converting one website from its written script to its opposite for both users and web developer. for instance, if website is designed using Latin characters, this algorithm converts to its opposite programmatically. The algorithm uses JavaScript language and configured on jQuery plugin for web developers as API (Application User Interface) to use in website. In addition, there is a Firefox browser add-ons (Extension) for users (non- developers) to convert script to its opposite. This research addresses cases (irregular cases) which cause to increase misspellings, then, find solutions for each of these cases to minimal incorrect spelling. To Increase accuracy of algorithm, one website chooses as case study for analyzing algorithm output. The algorithm is tested using test methods to check errors, debugging, and accuracy.

User-Generated Captions: From Hackers, to the Disability Digerati, to Fansubbers

User-Generated Captions: From Hackers, to the Disability Digerati, to Fansubbers

Reusable Client-Side JavaScript Modules for Immersive Web-Based Real-Time Collaborative Neuroimage Visualization.

In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView, a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution.

Facebook Inspector (FbI): Towards automatic real-time detection of malicious content on Facebook

Online Social Networks witness a rise in user activity whenever a major event makes news. Cyber criminals exploit this spur in user engagement levels to spread malicious content that compromises system reputation, causes financial losses and degrades user experience. In this paper, we collect and characterize a dataset of 4.4 million public posts generated on Facebook during 17 news-making events (natural calamities, sports, terror attacks, etc.) over a 16-month time period. From this dataset, we filter out two sets of malicious posts, one using URL blacklists and another using human annotations. Our observations reveal some characteristic differences between malicious posts obtained from the two methodologies, thus demanding a twofold filtering process for a more complete and robust filtering system. We empirically confirm the need for this twofold filtering approach by cross-validating supervised learning models obtained from the two sets of malicious posts. These supervised learning models include Naive Bayesian, Decision Trees, Random Forest, and Support Vector Machine-based models. Based on this learning, we implement Facebook Inspector, a REST API-based browser plug-in for identifying malicious Facebook posts in real time. Facebook Inspector uses class probabilities obtained from two independent supervised learning models based on a Random Forest classifier to identify malicious posts in real time. These supervised learning models are based on a feature set comprising of 44 features and achieve an accuracy of over 80% each, using only publicly available features. During the first 9 months of its public deployment (August 2015–May 2016), Facebook Inspector processed 0.97 million posts at an average response time of 2.6 s per post and was downloaded over 2500 times. We also evaluate Facebook Inspector in terms of performance and usability to identify further scope for improvement.

Analysis of Web Spam for Non-English Content: Toward More Effective Language-Based Classifiers.

Web spammers aim to obtain higher ranks for their web pages by including spam contents that deceive search engines in order to include their pages in search results even when they are not related to the search terms. Search engines continue to develop new web spam detection mechanisms, but spammers also aim to improve their tools to evade detection. In this study, we first explore the effect of the page language on spam detection features and we demonstrate how the best set of detection features varies according to the page language. We also study the performance of Google Penguin, a newly developed anti-web spamming technique for their search engine. Using spam pages in Arabic as a case study, we show that unlike similar English pages, Google anti-spamming techniques are ineffective against a high proportion of Arabic spam pages. We then explore multiple detection features for spam pages to identify an appropriate set of features that yields a high detection accuracy compared with the integrated Google Penguin technique. In order to build and evaluate our classifier, as well as to help researchers to conduct consistent measurement studies, we collected and manually labeled a corpus of Arabic web pages, including both benign and spam pages. Furthermore, we developed a browser plug-in that utilizes our classifier to warn users about spam pages after clicking on a URL and by filtering out search engine results. Using Google Penguin as a benchmark, we provide an illustrative example to show that language-based web spam classifiers are more effective for capturing spam contents.

Hypothes.is

As more historical work finds a home in digital spaces and as many history classes assign digital alternatives to traditional papers, tools that allow commenting on digital media are becoming increasingly valuable. Hypothes.is—designed as a platform to make the internet annotatable—is one of the most recent iterations of this kind of tool. The mission of the nonprofit organization behind the tool—also called Hypothes.is—is “to enable a conversation over the world's knowledge.” Hypothes.is allows public, sentence-level annotation of the internet in service of open critique and collaborative note taking and allows annotation in private groups to facilitate conversation for more limited audiences. Hypothes.is has a fairly low barrier to entry. User accounts are required but are free and can be pseudonymous. The program can be installed as a Chrome browser plugin, but users can also visit http://Hypothes.is and paste in the url of the page they want to annotate. Once the tool is launched, a sidebar allows users to highlight text, add annotations, read annotations that others have left on the same page, create private groups, and share the annotated page. While these functions have broad implications for public engagement, the features of Hypothes.is are also proving useful in history classrooms. For example, students in public history classes might use it to offer feedback on specific aspects of a digital archive. Faculty might use the private group feature to provide feedback on students' digital projects. Hypothes.is might alternately facilitate beta testing and peer review before those projects go “live.”