Searcharxiv⌕ Search

arXiv subjects

Nataliia Bielova

Publications and source records attributed to Nataliia Bielova.

17 recordsLinked to original sources
arXiv2026

SoK: Advances and Open Problems in Web Tracking

Web tracking is a pervasive and opaque practice that enables personalized advertising, retargeting, and conversion tracking. Over time, it has evolved into a sophisticated and invasive ecosystem, employing increasingly complex techniques to monitor and profile users across the web. The research community has a long track record of analyzing new web tracking techniques, designing and evaluating the effectiveness of countermeasures, and assessing compliance with privacy regulations. Despite a substantial body of work on web tracking, the literature remains fragmented across distinctly scoped studies, making it difficult to identify overarching trends, connect new but related techniques, and identify research gaps in the field. Today, web tracking is undergoing a transformation, driven by fundamental shifts in the advertising industry, the adoption of anti-tracking countermeasures by browsers, and the growing enforcement of emerging privacy regulations. This Systematization of Knowledge (SoK) aims to consolidate and synthesize this wide-ranging research, offering a comprehensive overview of the technical mechanisms, countermeasures, and regulations that shape the modern and rapidly evolving web tracking landscape. This SoK also highlights open challenges and outlines directions for future research.

cs.CR↗
arXiv2026

Beyond Epsilon: A Principled QIF Framework for Local Differential Privacy

Local Differential Privacy (LDP) has become the de facto standard for privacy-preserving data collection in large-scale systems, in particular for the purpose of estimating frequencies. However, the current research landscape lacks a systematic and principled way to compare LDP protocols. The parameter $\varepsilon$ of LDP is considered the measure of privacy, but it only bounds worst-case distinguishability. Other comparisons rely on utility-driven analyses, where mechanisms are ranked based on their ability to preserve data utility for a given privacy budget $\varepsilon$. Both such kinds of comparisons fail to account for the strength of protocols against diverse attacker models. In this paper, we propose a framework for analyzing LDP frequency estimation protocols through the lens of Quantitative Information Flow (QIF). By modeling LDP mechanisms as probabilistic channels, we leverage the concept of refinement (Blackwell ordering) to establish more principled classifications. This approach allows us to determine when one protocol is intrinsically superior to another for all possible adversaries, and to discuss the implications for utility. In particular, our analysis uncovers cases where protocols previously deemed "optimal" are, in fact, incomparable with, or strictly dominated by, other protocols. We provide a formal QIF-based treatment of seven state-of-the-art protocols, including Generalized Randomized Response (GRR), local hashing variants (BLH, OLH), unary encoding schemes (SUE, OUE), and Thresholding with Histogram Encoding (THE). This perspective bridges the gap between the LDP and formal methods communities and enables principled, adversary-aware reasoning about locally private systems.

cs.CR↗
arXiv2025

You Can't Trust Your Tag Neither: Privacy Leaks and Potential Legal Violations within the Google Tag Manager

Tag Management Systems were developed in order to support website publishers in installing multiple third-party JavaScript scripts (Tags) on their websites. Google developed its own TMS called ``Google Tag Manager'' (GTM) that is currently present on 42\% of the top 1 million most popular websites. However, GTM has not yet been thoroughly evaluated by the academic research community. In this work, we study, for the first time, the Tags provided within the GTM system. We propose a new methodology called ``detecting privacy leaks in isolation'' and apply it to multiple Tags to analyse the types of data that Tags collect and contrast them to the legal and technical documentation, in collaboration with a legal expert. Across three studies - in-depth analysis of 6 Tags, automated analysis of 718 Tags, and analysis of Google ``Consent Mode'' - we discover multiple hidden data leaks, incomplete and diverging declarations, undisclosed third-parties and cookies, personal data sharing without consent and we further identify potential legal violations within EU Data Protection law.

cs.CR↗
arXiv2025

Measuring Compliance of Consent Revocation on the Web

The GDPR requires websites to facilitate the right to revoke consent from Web users. While numerous studies measured compliance of consent with the various consent requirements, no prior work has studied consent revocation on the Web. Therefore, it remains unclear how difficult it is to revoke consent on the websites' interfaces, nor whether revoked consent is properly stored and communicated behind the user interface. Our work aims to fill this gap by measuring compliance of consent revocation on the Web on the top-200 websites. We found that 19.87% of websites make it difficult for users to revoke consent throughout different interfaces, 20.5% of websites require more effort than acceptance, and 2.48% do not provide consent revocation at all, thus violating legal requirements for valid consent. 57.5% websites do not delete the cookies after consent revocation enabling continuous illegal processing of users' data. Moreover, we analyzed 281 websites implementing the IAB Europe TCF, and found 22 websites that store a positive consent despite user's revocation. Surprisingly, we found that on 101 websites, third parties that have received consent upon user's acceptance, are not informed of user's revocation, leading to the illegal processing of users' data by such third parties. Our findings emphasise the need for improved legal compliance of consent revocation, and proper, consistent, and uniform implementation of revocation communication and data deletion practices.

cs.CR↗
arXiv2023

An Ontology of Dark Patterns Knowledge: Foundations, Definitions, and a Pathway for Shared Knowledge-Building

Deceptive and coercive design practices are increasingly used by companies to extract profit, harvest data, and limit consumer choice. Dark patterns represent the most common contemporary amalgamation of these problematic practices, connecting designers, technologists, scholars, regulators, and legal professionals in transdisciplinary dialogue. However, a lack of universally accepted definitions across the academic, legislative and regulatory space has likely limited the impact that scholarship on dark patterns might have in supporting sanctions and evolved design practices. In this paper, we seek to support the development of a shared language of dark patterns, harmonizing ten existing regulatory and academic taxonomies of dark patterns and proposing a three-level ontology with standardized definitions for 65 synthesized dark patterns types across low-, meso-, and high-level patterns. We illustrate how this ontology can support translational research and regulatory action, including pathways to extend our initial types through new empirical work and map across application domains.

cs.HC↗
arXiv2021

Did I delete my cookies? Cookies respawning with browser fingerprinting

Stateful and stateless web tracking gathered much attention in the last decade, however they were always measured separately. To the best of our knowledge, our study is the first to detect and measure cookie respawning with browser and machine fingerprinting. We develop a detection methodology that allows us to detect cookies dependency on browser and machine features. Our results show that 1,150 out of the top 30, 000 Alexa websites deploy this tracking mechanism. We further uncover how domains collaborate to respawn cookies through fingerprinting. We find out that this technique can be used to track users across websites even when third-party cookies are deprecated. Together with a legal scholar, we conclude that cookie respawning with browser fingerprinting lacks legal interpretation under the GDPR and the ePrivacy directive, but its use in practice may breach them, thus subjecting it to fines up to 20 million euro.

cs.CR↗
arXiv2021

Consent Management Platforms under the GDPR: processors and/or controllers?

Consent Management Providers (CMPs) provide consent pop-ups that are embedded in ever more websites over time to enable streamlined compliance with the legal requirements for consent mandated by the ePrivacy Directive and the General Data Protection Regulation (GDPR). They implement the standard for consent collection from the Transparency and Consent Framework (TCF) (current version v2.0) proposed by the European branch of the Interactive Advertising Bureau (IAB Europe). Although the IAB's TCF specifications characterize CMPs as data processors, CMPs factual activities often qualifies them as data controllers instead. Discerning their clear role is crucial since compliance obligations and CMPs liability depend on their accurate characterization. We perform empirical experiments with two major CMP providers in the EU: Quantcast and OneTrust and paired with a legal analysis. We conclude that CMPs process personal data, and we identify multiple scenarios wherein CMPs are controllers.

cs.HC↗
arXiv2021

Dark Patterns and the Legal Requirements of Consent Banners: An Interaction Criticism Perspective

User engagement with data privacy and security through consent banners has become a ubiquitous part of interacting with internet services. While previous work has addressed consent banners from either interaction design, legal, and ethics-focused perspectives, little research addresses the connections among multiple disciplinary approaches, including tensions and opportunities that transcend disciplinary boundaries. In this paper, we draw together perspectives and commentary from HCI, design, privacy and data protection, and legal research communities, using the language and strategies of "dark patterns" to perform an interaction criticism reading of three different types of consent banners. Our analysis builds upon designer, interface, user, and social context lenses to raise tensions and synergies that arise together in complex, contingent, and conflicting ways in the act of designing consent banners. We conclude with opportunities for transdisciplinary dialogue across legal, ethical, computer science, and interactive systems scholarship to translate matters of ethical concern into public policy.

cs.HC↗
arXiv2020

Are cookie banners indeed compliant with the law? Deciphering EU legal requirements on consent and technical means to verify compliance of cookie banners

In this work, we analyze the legal requirements on how cookie banners are supposed to be implemented to be fully compliant with the e-Privacy Directive and the General Data Protection Regulation. Our contribution resides in the definition of seventeen operational and fine-grained requirements on cookie banner design that are legally compliant, and moreover, we define whether and when the verification of compliance of each requirement is technically feasible. The definition of requirements emerges from a joint interdisciplinary analysis composed of lawyers and computer scientists in the domain of web tracking technologies. As such, while some requirements are provided by explicitly codified legal sources, others result from the domain-expertise of computer scientists. In our work, we match each requirement against existing cookie banners design of websites. For each requirement, we exemplify with compliant and non-compliant cookie banners. As an outcome of a technical assessment, we verify per requirement if technical (with computer science tools) or manual (with any human operator) verification is needed to assess compliance of consent and we also show which requirements are impossible to verify with certainty in the current architecture of the Web. For example, we explain how the requirement for revocable consent could be implemented in practice: when consent is revoked, the publisher should delete the consent cookie and communicate the withdrawal to all third parties who have previously received consent. With this approach we aim to support practically-minded parties (compliance officers, regulators, researchers, and computer scientists) to assess compliance and detect violations in cookie banner design and implementation, specially under the current revision of the European Union e-Privacy framework.

cs.CR↗
arXiv2020

DESIRE: A Third Way for a European Exposure Notification System Leveraging the best of centralized and decentralized systems

This document presents an evolution of the ROBERT protocol that decentralizes most of its operations on the mobile devices. DESIRE is based on the same architecture than ROBERT but implements major privacy improvements. In particular, it introduces the concept of Private Encounter Tokens, that are secret and cryptographically generated, to encode encounters. In the DESIRE protocol, the temporary Identifiers that are broadcast on the Bluetooth interfaces are generated by the mobile devices providing more control to the users about which ones to disclose. The role of the server is merely to match PETs generated by diagnosed users with the PETs provided by requesting users. It stores minimal pseudonymous data. Finally, all data that are stored on the server are encrypted using keys that are stored on the mobile devices, protecting against data breach on the server. All these modifications improve the privacy of the scheme against malicious users and authority. However, as in the first version of ROBERT, risk scores and notifications are still managed and controlled by the server of the health authority, which provides high robustness, flexibility, and efficacy.

cs.CR↗
arXiv2020

Missed by Filter Lists: Detecting Unknown Third-Party Trackers with Invisible Pixels

Web tracking has been extensively studied over the last decade. To detect tracking, previous studies and user tools rely on filter lists. However, it has been shown that filter lists miss trackers. In this paper, we propose an alternative method to detect trackers inspired by analyzing behavior of invisible pixels. By crawling 84,658 webpages from 8,744 domains, we detect that third-party invisible pixels are widely deployed: they are present on more than 94.51% of domains and constitute 35.66% of all third-party images. We propose a fine-grained behavioral classification of tracking based on the analysis of invisible pixels. We use this classification to detect new categories of tracking and uncover new collaborations between domains on the full dataset of 4,216,454 third-party requests. We demonstrate that two popular methods to detect tracking, based on EasyList&EasyPrivacy and on Disconnect lists respectively miss 25.22% and 30.34% of the trackers that we detect. Moreover, we find that if we combine all three lists 379,245 requests originated from 8,744 domains still track users on 68.70% of websites.

cs.CR↗
arXiv2020

Do Cookie Banners Respect my Choice? Measuring Legal Compliance of Banners from IAB Europe's Transparency and Consent Framework

As a result of the GDPR and the ePrivacy Directive, European users encounter cookie banners on almost every website. Many of such banners are implemented by Consent Management Providers (CMPs), who respect the IAB Europe's Transparency and Consent Framework (TCF). Via cookie banners, CMPs collect and disseminate user consent to third parties. In this work, we systematically study IAB Europe's TCF and analyze consent stored behind the user interface of TCF cookie banners. We analyze the GDPR and the ePrivacy Directive to identify legal violations in implementations of cookie banners based on the storage of consent and detect such violations by crawling 22 949 European websites. With two automatic and semi-automatic crawl campaigns, we detect violations, and we find that: 141 websites register positive consent even if the user has not made their choice; 236 websites nudge the users towards accepting consent by pre-selecting options; and 27 websites store a positive consent even if the user has explicitly opted out. Performing extensive tests on 560 websites, we find at least one violation in 54% of them. Finally, we provide a browser extension to facilitate manual detection of violations for regular users and Data Protection Authorities.

cs.CR↗
arXiv2019

Browser Fingerprinting: A survey

With this paper, we survey the research performed in the domain of browser fingerprinting, while providing an accessible entry point to newcomers in the field. We explain how this technique works and where it stems from. We analyze the related work in detail to understand the composition of modern fingerprints and see how this technique is currently used online. We systematize existing defense solutions into different categories and detail the current challenges yet to overcome.

cs.CR↗
arXiv2018

To Extend or not to Extend: on the Uniqueness of Browser Extensions and Web Logins

Recent works showed that websites can detect browser extensions that users install and websites they are logged into. This poses significant privacy risks, since extensions and Web logins that reflect user's behavior, can be used to uniquely identify users on the Web. This paper reports on the first large-scale behavioral uniqueness study based on 16,393 users who visited our website. We test and detect the presence of 16,743 Chrome extensions, covering 28% of all free Chrome extensions. We also detect whether the user is connected to 60 different websites. We analyze how unique users are based on their behavior, and find out that 54.86% of users that have installed at least one detectable extension are unique; 19.53% of users are unique among those who have logged into one or more detectable websites; and 89.23% are unique among users with at least one extension and one login. We use an advanced fingerprinting algorithm and show that it is possible to identify a user in less than 625 milliseconds by selecting the most unique combinations of extensions. Because privacy extensions contribute to the uniqueness of users, we study the trade-off between the amount of trackers blocked by such extensions and how unique the users of these extensions are. We have found that privacy extensions should be considered more useful than harmful. The paper concludes with possible countermeasures.

cs.CR↗
arXiv2017

Control What You Include! Server-Side Protection against Third Party Web Tracking

Third party tracking is the practice by which third parties recognize users accross different websites as they browse the web. Recent studies show that 90% of websites contain third party content that is tracking its users across the web. Website developers often need to include third party content in order to provide basic functionality. However, when a developer includes a third party content, she cannot know whether the third party contains tracking mechanisms. If a website developer wants to protect her users from being tracked, the only solution is to exclude any third-party content, thus trading functionality for privacy. We describe and implement a privacy-preserving web architecture that gives website developers a control over third party tracking: developers are able to include functionally useful third party content, the same time ensuring that the end users are not tracked by the third parties.

cs.CR↗
arXiv2017

On the Content Security Policy Violations due to the Same-Origin Policy

Modern browsers implement different security policies such as the Content Security Policy (CSP), a mechanism designed to mitigate popular web vulnerabilities, and the Same Origin Policy (SOP), a mechanism that governs interactions between resources of web pages. In this work, we describe how CSP may be violated due to the SOP when a page contains an embedded iframe from the same origin. We analyse 1 million pages from 10,000 top Alexa sites and report that at least 31.1% of current CSP-enabled pages are potentially vulnerable to CSP violations. Further considering real-world situations where those pages are involved in same-origin nested browsing contexts, we found that in at least 23.5% of the cases, CSP violations are possible. During our study, we also identified a divergence among browsers implementations in the enforcement of CSP in srcdoc sandboxed iframes, which actually reveals a problem in Gecko-based browsers CSP implementation. To ameliorate the problematic conflicts of the security mechanisms, we discuss measures to avoid CSP violations.

cs.CR↗