Refine
Document Type
- Conference Proceeding (3)
- Article (2)
Has Fulltext
- no (5)
Is part of the Bibliography
- no (5)
Keywords
- privacy (2)
- HbbTV (1)
- IT security (1)
- bibliometrics (1)
- coauthorship networks (1)
- consent banner (1)
- cookie banner (1)
- cookies (1)
- cybersecurity (1)
- metascience (1)
Institute
Hybrid broadcast broadband television (HbbTV) is an evolving technology that connects linear TV with modern HTML5 applications, delivering extras like games, videos, and online shopping. However, its bidirectional transmission functionality raises privacy concerns, as it introduces new tracking methods for TV channels. While previous studies focused on security issues or user awareness of HbbTV privacy challenges, a detailed examination of the tracking and transparency mechanisms of the HbbTV ecosystem is still missing. This study fills this gap by extensively analyzing these features within the European HbbTV ecosystem, and in particular within German-language TV channels. We monitored more than 350 TV channels for over 400 hours, evaluating 1) prevalent HbbTV tracking methods, 2) consent notice prevalence and user interactions, and 3) privacy policy disclosures. Our findings indicate that the HbbTV tracking system operates independently of the Web, consent notices exploit system constraints to influence users, and privacy policies often do not align with actual data practices.
Four decades of security and privacy research: evolution of topics, impact, and the community
(2026)
As digital technologies become increasingly embedded in societal infrastructure, IT security and privacy (S&P) have become critical for protecting sensitive information and preserving trust. These domains have evolved from foundational security measures to address complex challenges introduced by artificial intelligence, regulatory frameworks, and decentralized technologies. This paper presents a longitudinal analysis of the evolution of IT S&P research from 1980 to 2023, analyzing over 13k papers from the most relevant venues. Employing the frameworks of established theories from social sciences, i.e. Latour’s actor–network theory, and Bourdieu’s forms of capital, along with Leydesdorff’s key dimensions in scientometrics, we discuss the evolution of research topics and highlight research priorities in the past and today. We apply modern natural language processing techniques to build a taxonomy of research topics within the S&P community. Using this taxonomy, we analyze the community’s thematic development, tracing its growth from 5 topics in the 1980s to 100 distinct research topics, reflecting the field’s expanding scope and complexity. Analyzing 0.5M authors, we demonstrate strong collaboration networks in the IT S&P community. We also demonstrate that the proportion of female authors in this community has remained relatively constant over the decades, despite an increase in their research activity in recent years. Finally, we assess factors impacting paper citations, author networks, and the linguistic evolution of the community. This study enhances the understanding of the S&P research community, providing valuable insights into future directions. The data underlying this article, including the analysis code and data processing pipeline, are available in the repository at: https://pulse-of-cybersecurity.com/, which also provides an interactive webpage for exploring our results.
Web measurement studies can shed light on not yet fully understood phenomena and thus are essential for analyzing how the modern Web works. This often requires building new and adjustinng existing crawling setups, which has led to a wide variety of analysis tools for different (but related) aspects. If these efforts are not sufficiently documented, the reproducibility and replicability of the measurements may suffer—two properties that are crucial to sustainable research. In this paper, we survey 117 recent research papers to derive best practices for Web-based measurement studies and specify criteria that need to be met in practice. When applying these criteria to the surveyed papers, we find that the experimental setup and other aspects essential to reproducing and replicating results are often missing. We underline the criticality of this finding by performing a large-scale Web measurement study on 4.5 million pages with 24 different measurement setups to demonstrate the influence of the individual criteria. Our experiments show that slight differences in the experimental setup directly affect the overall results and must be documented accurately and carefully.
Measurement studies are essential for research and industry alike to understand the Web’s inner workings better and help quantify specific phenomena. Performing such studies is demanding due to the dynamic nature and size of the Web. An experiment’s careful design and setup are complex, and many factors might affect the results. However, while several works have independently observed differences in
the outcome of an experiment (e.g., the number of observed trackers) based on the measurement setup, it is unclear what causes such deviations. This work investigates the reasons for these differences by visiting 1.7M webpages with five different measurement setups. Based on this, we build ‘dependency trees’ for each page and cross-compare the nodes in the trees. The results show that the measured trees differ considerably, that the cause of differences can be attributed to specific nodes, and that even identical measurement setups can produce different results.
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.

