Alexandros Kapravelos

dblp:22/1459 · DBLP profile ↗
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5ranked-venue papers in the field
0as first author
4since 2021 · last 2023
0000-0002-8839-8521ORCID · verified

Domains — venue-derived; a paper can count in several

Information Retrieval & Web Search · 5
YearPublicationVenuePosition
2023 Automatic Discovery of Emerging Browser Fingerprinting Techniques
abstract
With the progression of modern browsers, online tracking has become the most concerning issue for preserving privacy on the web. As major browser vendors plan to or already ban third-party cookies, trackers have to shift towards browser fingerprinting by incorporating novel browser APIs into their tracking arsenal. Understanding how new browser APIs are abused in browser fingerprinting techniques is a significant step toward ensuring protection from online tracking.
Junhua Su, Alexandros Kapravelos
WWW2
2022 Measuring the Privacy vs. Compatibility Trade-off in Preventing Third-Party Stateful Tracking
abstract
Despite active privacy research on sophisticated web tracking techniques (e.g., fingerprinting, cache collusion, bounce tracking, CNAME cloaking), most tracking on the web is basic “stateful” tracking enabled by classical browser storage policies sharing per-site storage across all HTTP contexts. Alternative, privacy-preserving storage policies, especially for third-party contexts, have been proposed and even deployed, but these can break websites that presume traditional, non-partitioned storage. Such breakage discourages privacy-preserving experimentation, cementing the dismal status quo. Our work measures the privacy vs. compatibility trade-offs of representative third-party storage policies to enable design of browsers that are both compatible and privacy respecting. Our contributions include web-scale measurements of page behaviors under multiple third-party storage policies inspired by production browsers. We define metrics for measuring aggregate effects on web privacy and compatibility, including a novel system for quantitatively estimating aggregate website breakage under different policies. We find that making third-party storage partitioned by first-party, and lifetimes by site-session achieves the best privacy and compatibility trade-off. We provide complete measurement datasets and storage policy implementations.
Jordan Jueckstock, Peter Snyder, Shaown Sarker, Alexandros Kapravelos, Benjamin Livshits
WWW4
2021 Cookie Swap Party: Abusing First-Party Cookies for Web Tracking
abstract
As a step towards protecting user privacy, most web browsers perform some form of third-party HTTP cookie blocking or periodic deletion by default, while users typically have the option to select even stricter blocking policies. As a result, web trackers have shifted their efforts to work around these restrictions and retain or even improve the extent of their tracking capability.
Panagiotis Ilia, Michalis Polychronakis, Alexandros Kapravelos
WWW4
2021 Towards Realistic and ReproducibleWeb Crawl Measurements
abstract
Accurate web measurement is critical for understanding and improving security and privacy online. Such measurements implicitly assume that automated crawls generalize to typical web user experience. But anecdotal evidence suggests the web behaves differently when seen via well-known measurement endpoints or measurement automation frameworks, for various reasons. Our work improves the state of web privacy and security by investigating how key measurements differ when using naive crawling tool defaults vs. careful attempts to match “real” users across the Tranco top 25k web domains. We find web privacy and security measurements significantly affected by vantage point and browser configuration. We conclude that unless researchers ensure their web measurement tools match real world user experience, the research community is likely missing important signals systematically. For example, we find browser configuration alone causing shifts in 19% of known ad and tracking domains encountered and altering the loading frequency of up to 10% of distinct JavaScript code units executed. We find network vantage point having similar, though less dramatic, effects on the same web metrics. To ensure reproducibility, we carefully document our methodology and publish both our code and collected data.
Jordan Jueckstock, Shaown Sarker, Peter Snyder, Aidan Beggs, Panagiotis Papadopoulos, Matteo Varvello, Benjamin Livshits, Alexandros Kapravelos
WWW8
2019 Unnecessarily Identifiable: Quantifying the fingerprintability of browser extensions due to bloat
abstract
In this paper, we investigate to what extent the page modifications that make browser extensions fingerprintable are necessary for their operation. We characterize page modifications that are completely unnecessary for the extension's functionality as extension bloat. By analyzing 58,034 extensions from the Google Chrome store, we discovered that 5.7% of them were unnecessarily identifiable because of extension bloat. To protect users against unnecessary extension fingerprinting due to bloat, we describe the design and implementation of an in-browser mechanism that provides coarse-grained access control for extensions on all websites. The proposed mechanism and its built-in policies, does not only protect users from fingerprinting, but also offers additional protection against malicious extensions exfiltrating user data from sensitive websites.
Oleksii Starov, Pierre Laperdrix, Alexandros Kapravelos, Nick Nikiforakis
WWW3