Browser Extension Research Articles

Access broker browser extensions: plugin tools for searching open scholarly literature

Purpose This study aims to explore browsing extension plugins for searching open scholarly literature and gain an understanding of the various available extensions, their functionalities and their benefits. Design/methodology/approach Instant retrieval of scholarly literature on the internet is challenging for any researcher due to incredibly accessible free and paid content, including various forms of resources, despite the availability of federated and discovery tools. This paper aimed to explore “Access Broker Browser extensions” available for quick retrieval of open scholarly literature. This paper explicitly explains browser extensions – Google Scholar Button, Open Access Button, Open Access Helper, Core, GetFTR and EndNote Click. Furthermore, the paper elaborated on the extension’s features, functionalities and usability in finding scholarly literature. This study found that the Google Scholar Button and GetFTR extensions seems more user-friendly, effective and easy to use on all internet browsers. Findings This paper identifies that the “Google Scholar Button” and “GetFTR” browser extensions are more effective than any other extensions and very user-friendly to use. Originality/value This study recommends that libraries should create awareness and provide training on access broker browser extensions for discovering scholarly open literature for learning.

A Large-Scale Study of Cookie Banner Interaction Tools and their Impact on Users' Privacy

Cookie notices (or cookie banners) are a popular mechanism for websites to provide (European) Internet users a tool to choose which cookies the site may set. Banner implementations range from merely providing information that a site uses cookies over offering the choice to accepting or denying all cookies to allowing fine-grained control of cookie usage. Users frequently get annoyed by the banner's pervasiveness as they interrupt ''natural'' browsing on the Web. As a remedy, different browser extensions have been developed to automate the interaction with cookie banners. In this work, we perform a large-scale measurement study comparing the effectiveness of extensions for ''cookie banner interaction.'' We configured the extensions to express different privacy choices (e.g., accepting all cookies, accepting functional cookies, or rejecting all cookies) to understand their capabilities to execute a user's preferences. The results show statistically significant differences in which cookies are set, how many of them are set, and which types are set---even for extensions that aim to implement the same cookie choice. Extensions for ''cookie banner interaction'' can effectively reduce the number of set cookies compared to no interaction with the banners. However, all extensions increase the tracking requests significantly except when rejecting all cookies.

Generalizable Active Privacy Choice: Designing a Graphical User Interface for Global Privacy Control

The California Consumer Privacy Act and other privacy laws give people a right to opt out of the sale and sharing of personal information. In combination with privacy preference signals, especially, Global Privacy Control (GPC), such rights have the potential to empower people to assert control over their data. However, many laws prohibit opt out settings being turned on by default. The resulting usability challenges for people to exercise their rights motivate generalizable active privacy choice --- an interface design principle to make opt out settings usable without defaults. It is based on the idea of generalizing one individual opt out choice towards a larger set of choices. For example, people may apply an opt out choice on one site towards a larger set of sites. We explore generalizable active privacy choice in the context of GPC. We design and implement nine privacy choice schemes in a browser extension and explore them in a usability study with 410 participants. We find that generalizability features tend to decrease opt out utility slightly. However, at the same time, they increase opt out efficiency and make opting out less disruptive, which was more important to most participants. For the least disruptive scheme, selecting website categories to opt out from, 98% of participants expressed not feeling disrupted, a 40% point increase over the baseline schemes. 83% of participants understood the meaning of GPC. They also made their opt out choices with intent and, thus, in a legally relevant manner. To help people exercise their opt out rights via GPC our results support the adoption of a generalizable active privacy choice interface in web browsers.

Block Cookies, Not Websites: Analysing Mental Models and Usability of the Privacy-Preserving Browser Extension CookieBlock

In the modern web, users are confronted with a plethora of complex privacy-related decisions about cookies and consent, often com- pounded by misleading policies and deceptive patterns. Past efforts to enhance online privacy have failed due to their dependence on website compliance. A solution to this lies in privacy-enhancing tools that are directly controlled by the user. However, challenges related to the usability and flawed understanding of the tools’ func- tionality hinder their widespread adoption. To address this problem, we evaluated the browser extension CookieBlock as an example of a current tool, which supports users by blocking tracking cookies independent of website compliance. We used a complementary approach consisting of an expert eval- uation of CookieBlock and the related tools NoScript and Ghostery, and a laboratory user study focusing on the unique details of how users interact with CookieBlock specifically. The laboratory study with 42 participants investigated usage, mental models, and us- ability of CookieBlock based on eye tracking, interaction, and self- report data. While CookieBlock received good usability ratings, 18 participants were unable to solve a website breakage caused by cookie misclassification on their own. Overall, the results revealed flawed mental models of CookieBlock’s functionality and resulting challenges in making the connection between website breakage and cookie misclassification. Implications for CookieBlock and related applications include interface design recommendations supporting accurate mental models and the proposal of improved heuristics to better guide users and warn them about potential identified website breakage.

CLASSIFICATION AND METHODS OF DETECTION OF PHISHING ATTACKS

The reliable operation of data transmission networks, computer systems and mobile devices is a mandatory condition for the effective functioning of the state and society, and the life of an individual. The reliability of key information systems for public use depends on many factors: cyber attacks, hardware and software failures, and various types of errors. Rapid expansion of threats to national security in the 21st century. entrusts state authorities with the tasks of their prevention, detection and neutralization. Cyber security is increasingly viewed as a fundamental problem of the state, which comprehensively affects its security, defense, economy, and almost all spheres of public life. The Internet gave a powerful impetus to the development of mass communication, trade and information exchange. However, today it is the area where many crimes are committed. The impersonal nature of digital infrastructure has made identity theft a natural and highly attractive project. Cybercriminals actively use various means of stealing information, including phishing. At the current stage and in the future, the development of both individual societies and states, as well as the world in general, will be carried out in accordance with the concept of the information society, which is connected with the use of information and telecommunication technologies in the acquisition, storage and processing of information in everyday life Phishing is a serious online security problem that involves spoofing genuine websites to trick online users and steal their confidential information. Analyzing these definitions, we can conclude that “phishing” can be considered in different ways, but the main purpose of its conduct remains unchanged—stealing data. The practical value of the results lies in the possibility of using the obtained classifier for further creation of software solutions for recognizing phishing sites. It, as well as a set of characteristics, can be implemented in anti-phishing browser extensions or other anti-phishing tools.

Analyzing Security Risks in Browser Extension Search Tools: A Literature Review

Analyzing Security Risks in Browser Extension Search Tools: A Literature Review

Prevention of URL Attacks by Analyzing Browser Extension

Prevention of URL Attacks by Analyzing Browser Extension

Development of Hash-Based Multi-Factor Password Generating System

The use of passwords or passphrases is essential for every internet user. However, users often face a dilemma between choosing simple passwords that are easy to crack and complex passwords that are difficult to remember, leading to frequent and cumbersome password recovery processes. This paper focuses on addressing this issue by developing a multifactor, unique password-generating system using SHA-256. The system incorporates factors such as a Unique Identifier, a biometric key value, and an Android mobile phone with a Biometric scanner. To accomplish this, an algorithm is devised using JavaScript that concatenates and generates a hash value by applying the SHA-256 algorithm to the Unique Identifier and Biometric Key values. The software implementation is achieved using the JavaScript programming language, with support from predefined plugins. Once the application is created, passwords can be generated by inputting a user's fingerprint ID and an Identifier (e.g., “Facebook.com”), resulting in the generation of a 32-character unique password. This process can be applied to any identifier and can reproduce the same password when the same factors are supplied. The experimentation results demonstrate that the system is capable of generating unique passwords for different platforms and can reproduce the same password for each platform if needed. While the focus of this paper is on the development of a system for Android mobile phone operating systems, It is suggested that its functionality be expanded by developing a browser extension and versions for other operating systems to improve its usability and accessibility across multiple platforms.

Online searches to evaluate misinformation can increase its perceived veracity.

Considerable scholarly attention has been paid to understanding belief in online misinformation1,2, with a particular focus on social networks. However, the dominant role of search engines in the information environment remains underexplored, even though the use of online search to evaluate the veracity of information is a central component of media literacy interventions3-5. Although conventional wisdom suggests that searching online when evaluating misinformation would reduce belief in it, there is little empirical evidence to evaluate this claim. Here, across five experiments, we present consistent evidence that online search to evaluate the truthfulness of false news articles actually increases the probability of believing them. To shed light on this relationship, we combine survey data with digital trace data collected using a custom browser extension. We find that the search effect is concentrated among individuals for whom search engines return lower-quality information. Our results indicate that those who search online to evaluate misinformation risk falling into data voids, or informational spaces in which there is corroborating evidence from low-quality sources. We also find consistent evidence that searching online to evaluate news increases belief in true news from low-quality sources, but inconsistent evidence that it increases belief in true news from mainstream sources. Our findings highlight the need for media literacy programmes to ground their recommendations in empirically tested strategies and for search engines to invest in solutions to the challenges identified here.

Predict2Protect: Machine Learning Web Application in Early Detection of Heart Disease.

Across the world, there are few universal scenarios, but the pain of losing a loved one to heart disease is an exception and a reality shared by millions every year. Heart disease is the greatest killer in society today, and one prevalent root of this issue is untimely diagnosis, often caused by unsustainable costs and lack of accessible healthcare for underserved populations. Recognizing these disparities, the goal of this project was to create an easily available application and interface for all that accurately indicates one's risk of heart disease. To address this, a machine learning model, Predict2Protect, was built in Python. An open-source dataset compiled of 1025 patients of diverse backgrounds was scaled, adjusted to include inquiries answerable by patients, and split into 75% for training, 15% for validation, and 25% for testing. Four models were tested with the hypothesis that if the RandomForestClassifier was used, it would have the highest validity. This was not supported, as the DecisionTree model had a 100% accuracy for training data and 95% for test data. Through the application software Streamlit, this program was processed into a web application that is now found in browser extensions. The application reports the risk of one having heart disease with a 95% accuracy and describes the risk percentage of developing heart disease within the next year. With a simple interface and high accuracy, Predict2Protect aims to provide a view into one's health with the goals of accessible heart disease prediction and early treatment for patients around the world.

Development of client applications on Blockchain

Objective. The article discusses issues related to the process of developing client Web applications for IT projects, which are based on the principles of decentralized network technology - blockchain. The authors explore practical ways to implement the user authorization process and its interaction with the blockchain network through a client application.Method. The MetaMask browser extension was chosen as a research tool, which allows you to develop, test and run your own software modules.Result. In the course of the study, the analysis of MetaMask tools was carried out, the processes associated with the start of work were considered both from the point of view of the developer and from the point of view of the wallet user. Understanding the organization of these processes will allow users to form the necessary knowledge in the development of client applications built on blockchain.Conclusion. The program code templates developed by the authors can be used as standard ones in the development of client applications in the decentralized Ethereum network. The advantage of the proposed solutions lies in the use of simple software structures that allow the formation of basic principles.

Crowdsourced audit of Twitter’s recommender systems

This research conducts an audit of Twitter’s recommender system, aiming to examine the disparities between users’ curated timelines and their subscription choices. Through the combined use of a browser extension and data collection via the Twitter API, our investigation reveals a high amplification of friends from the same community, a preference for amplifying emotionally charged and toxic tweets and an uneven algorithmic amplification across friends’ political leaning. This audit emphasizes the importance of transparency, and increased awareness regarding the impact of algorithmic curation.

Safeguard confidential web information from malicious browser extension using Encryption and Isolation techniques

Web browsers have become an integral part of our daily lives, granting us access to vast information and services. However, this convenience significantly risks personal information and data security. One common source of this risk is browser extensions, which users often employ to add new features to their browsers. Unfortunately, these extensions can also pose a security threat, as malicious ones may access and steal sensitive information such as passwords, credit card details, and personal data. The vulnerability of web browsers to malicious extensions is a significant challenge that effectively tackles through robust defence mechanisms. To address this concern, Secure Vault – API is proposed and designed to safeguard confidential web page content from malicious extensions. The Web Crypto API provides cryptographic functions that protect data during transmission and storage. The Secure Vault encompasses a Sentinel extension responsible for parsing the web page’s Document Object Model (DOM) content and querying for all “vault” elements. The extension then verifies that the DOM content has not been tampered with by any malicious extension by calculating the SHA512 hash value of the concatenated vault elements as a string, with no whitespace between them. With its encryption, hashing, and isolation techniques, the Secure Vault effectively protects confidential web page content from malicious extensions. It provides a secure environment for storing and processing sensitive data, reducing the risk of data breaches caused by malicious extensions. The proposed approach offers significant advantages over existing strategies in terms of protecting confidential web page content from malicious extensions. This not only improves the efficiency and effectiveness of the browser extensions but also ensures compatibility, interoperability and performance across different web browsers with respect to the load time of HTML elements. Users can browse the web and carry out sensitive transactions with peace of mind, knowing their data is safeguarded against theft or manipulation by malicious extensions.

Ensuring Privacy and Security on Banking Websites in Malaysia: A Cookies Scanner Solution

In this new era of science and technology, data can be said to be an extremely valuable asset for individuals, corporations, and even countries. Different parties attempt to obtain users' data occasionally, and the collection of web cookies is a prominent example. When users use a computer network, their data will be saved by the web server as cookies, including their private information. As people with bad intentions obtain this information, they can use it to commit cybercrimes and cause losses to the information owners. Thus, cookies management is vital for web users to protect their data. This paper proposes a cookies scanner for banking websites in Malaysia to help web users manage cookies. The scope is focused on banking websites as it is the most targeted website by cybercriminals. The proposed scanner will help users identify, understand, and manage cookies to keep their banking information safe. This paper explores existing cookie scanners to determine the proposed system's design and identify improvement areas. In this paper, we proposed a framework to develop the cookie scanner in the browser extension format. The system's access mode, workflow, functionalities, technical specifications, and requirements are discussed throughout the paper. To show our contribution, a copy of the proposed code implementation has been made available at https://github.com/gnohiy/cookies-scanner-for-banking-websites-in-malaysia.git.

Enabling Efficient Web Data-Record Interaction for People with Visual Impairments via Proxy Interfaces

Web data records are usually accompanied by auxiliary webpage segments, such as filters, sort options, search form, and multi-page links, to enhance interaction efficiency and convenience for end users. However, blind and visually impaired (BVI) persons are presently unable to fully exploit the auxiliary segments like their sighted peers, since these segments are scattered all across the screen, and as such assistive technologies used by BVI users, i.e., screen reader and screen magnifier, are not geared for efficient interaction with such scattered content. Specifically, for blind screen reader users, content navigation is predominantly one-dimensional despite the support for skipping content, and therefore navigating to-and-fro between different parts of the webpage is tedious and frustrating. Similarly, low vision screen magnifier users have to continuously pan back-and-forth between different portions of a webpage, given that only a portion of the screen is viewable at any instant due to content enlargement. The extant techniques to overcome inefficient web interaction for BVI users have mostly focused on general web-browsing activities, and as such they provide little to no support for data record-specific interaction activities such as filtering and sorting – activities that are equally important for facilitating quick and easy access to desired data records. To fill this void, we present InSupport, a browser extension that: (i) employs custom machine learning-based algorithms to automatically extract auxiliary segments on any webpage containing data records; and (ii) provides an instantly accessible proxy one-stop interface for easily navigating the extracted auxiliary segments using either basic keyboard shortcuts or mouse actions. Evaluation studies with 14 blind participants and 16 low vision participants showed significant improvement in web usability with InSupport, driven by increased reduction in interaction time and user effort, compared to the state-of-the-art solutions.

Impact of Social Reference Cues on Misinformation Sharing on Social Media: Series of Experimental Studies.

Health-related misinformation on social media is a key challenge to effective and timely public health responses. Existing mitigation measures include flagging misinformation or providing links to correct information, but they have not yet targeted social processes. Current approaches focus on increasing scrutiny, providing corrections to misinformation (debunking), or alerting users prospectively about future misinformation (prebunking and inoculation). Here, we provide a test of a complementary strategy that focuses on the social processes inherent in social media use, in particular, social reinforcement, social identity, and injunctive norms. This study aimed to examine whether providing balanced social reference cues (ie, cues that provide information on users sharing and, more importantly, not sharing specific content) in addition to flagging COVID-19-related misinformation leads to reductions in sharing behavior and improvement in overall sharing quality. A total of 3 field experiments were conducted on Twitter's native social media feed (via a newly developed browser extension). Participants' feed was augmented to include misleading and control information, resulting in 4 groups: no-information control, Twitter's own misinformation warning (misinformation flag), social cue only, and combined misinformation flag and social cue. We tracked the content shared or liked by participants. Participants were provided with social information by referencing either their personal network on Twitter or all Twitter users. A total of 1424 Twitter users participated in 3 studies (n=824, n=322, and n=278). Across all 3 studies, we found that social cues that reference users' personal network combined with a misinformation flag reduced the sharing of misleading but not control information and improved overall sharing quality. We show that this improvement could be driven by a change in injunctive social norms (study 2) but not social identity (study 3). Social reference cues combined with misinformation flags can significantly and meaningfully reduce the amount of COVID-19-related misinformation shared and improve overall sharing quality. They are a feasible and scalable way to effectively curb the sharing of COVID-19-related misinformation on social media.

FAKE NEWS DETECTION USING NATURAL LANGUAGE PROCESSING

Online social media plays an important role during real world events such as natural calamities, election s, social movements etc. Since the social media usage has increased, fake news has grown. The social media is often used by modifying true news or creating fake news to spread misinformation. The creation and distribution of fake news poses major threats in several respects from a national security point of view. Hence Fake news identification becomes an essential goal for enhancing the trustworthiness of the information shared on online social network. Over the period of time many researcher has used different methods, algorithms, tools and techniques to identify fake news content from online social networks. The aim of this paper is to review and examine these methodologies, different tools, browser extensions and analyze the degree of output in question. In addition, this paper discuss the general approach of fake news detection as well as taxonomy of feature extraction which plays an important role to achieve maximum accuracy with the help of different Machine Learning and Natural Language Processing algorithms. Keywords—Fake News Detection, Natural Language Processing, Online Social Network, Machine Learning, Sentiment Analysis.

Blocking JavaScript Without Breaking the Web: An Empirical Investigation

Modern websites heavily rely on JavaScript (JS) to implement legitimate functionality as well as privacy-invasive advertising and tracking. Browser extensions such as NoScript block any script not loaded by a trusted list of endpoints, thus hoping to block privacy-invasive scripts while avoiding breaking legitimate website functionality. In this paper, we investigate whether blocking JS on the web is feasible without breaking legitimate functionality. To this end, we conduct a large-scale measurement study of JS blocking on 100K websites. We evaluate the effectiveness of different JS blocking strategies in tracking prevention and functionality breakage. Our evaluation relies on quantitative analysis of network requests and resource loads as well as manual qualitative analysis of visual breakage. First, we show that while blocking all scripts is quite effective at reducing tracking, it significantly degrades functionality on approximately two-thirds of the tested websites. Second, we show that selective blocking of a subset of scripts based on a curated list achieves a better trade-off. However, there remain approximately 15% “mixed” scripts, which essentially merge tracking and legitimate functionality and thus cannot be blocked without causing website breakage. Finally, we show that fine-grained blocking of a subset of JS methods, instead of scripts, reduces major breakage by 3.8× while providing the same level of tracking prevention. Our work highlights the promise and open challenges in fine-grained JS blocking for tracking prevention without breaking the web.

Matt Frisbie on Browser Extensions

Matt Frisbie on Browser Extensions

Транслатологическое обоснование создания многоязычных ресурсов Интернета

The article analyses the determined character of forming multilingual Internet space in terms of the status of language in the system of world languages and in the set of languages of website content. Multilingualism is considered as a new stage in the development of web communication, replacing the brief periods of English dominance and the emergence of Internet segments in national languages. The tendency towards representation of content in different languages reflects an attitude towards considering users as participants in institutional discourses. The study uses the examples from material that has undergone a detailed interpretation stage in translation classes and during the preparation of final qualification papers by students in translation. The basis of translatological logistics of a multilingual resource consists in the fact that a site hypertext is objectively conditioned by a set of linguistic characteristics of the original content and the pragmatics of creating translated versions. Therefore, creating a global version in English involves not only changing the site structure, reducing texts and neutralising linguistic and cultural markings, but also ensuring that content is understandable to a wide audience owing to appropriate translation techniques application. Translation into German may be driven by marketing factors, French versions occur in response to high demands of linguistic "purism" in the state and society, while translation into Russian allows expanding the audience of potential users. It is revealed that the use of machine translation in the material reviewed is restricted by the purposes of the discourse and the sociopragmatics of the recipient of the translated version. The refusal to translate using a built-in browser extension reflects the sender's focus on effective communication and his desire to meet the recipient's "horizon of expectations". It is stated that the Internet space development is not determined by regulatory mechanisms, but by the orientation of resources towards the objectives of discourses and the needs and capabilities of their participants.