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Demo Data from EDBT 2026 / reviewers in the wild / expert

Abbie Farr

dblp:410/6086 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0004-1969-349XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Network security · 44% Web and mobile security · 44% Privacy and data protection · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network security › traffic analysis
device fingerprinting		 0.912025
Fingerprinting SDKs for Mobile Apps and Where to Find Them: Understanding the Market for Device Fingerprinting · CCS 2025
Web and mobile security
mobile application security		 0.912025
Fingerprinting SDKs for Mobile Apps and Where to Find Them: Understanding the Market for Device Fingerprinting · CCS 2025
Privacy and data protection
online tracking		 0.312025
Fingerprinting SDKs for Mobile Apps and Where to Find Them: Understanding the Market for Device Fingerprinting · CCS 2025

Methods — techniques the papers use, named apart from their topics

static analysis · 0.9
YearPublicationVenuePosition
2025 Fingerprinting SDKs for Mobile Apps and Where to Find Them: Understanding the Market for Device Fingerprinting
abstract
This paper presents a large-scale analysis of fingerprinting-like behavior in the mobile application ecosystem. We take a market-based approach, focusing on third-party tracking as enabled by applications' common use of third-party SDKs. Our dataset consists of over 228,000 SDKs from popular Maven repositories, 178,000 Android applications collected from the Google Play store, and our static analysis pipeline detects exfiltration of over 500 individual signals. To the best of our knowledge, this represents the largest-scale analysis of SDK behavior undertaken to date.
Michael A. Specter, Mihai Christodorescu, Abbie Farr, Bo Ma 0013, Robin Lassonde
 CCS3