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Maximilian Hils

dblp:169/9600 · DBLP profile ↗
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3ranked-venue papers
3as first author
1since 2021 · last 2021
0000-0003-2084-8095ORCID · corroborated

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

Security and privacy · 2 · 2 first-author · 1 since 2021Computer networks · 1 · 1 first-author

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
Privacy and data protection · 100%
Databases, data mining, and information retrieval
1 paper
Web and social media mining · 100%

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

TopicWeightPapersLastEvidence papers
Privacy and data protection › privacy compliance › consent
consent management
0.412020
Measuring the Emergence of Consent Management on the Web · Internet Measurement Conference 2020
Privacy and data protection › privacy compliance
GDPR compliance
0.412020
Measuring the Emergence of Consent Management on the Web · Internet Measurement Conference 2020
Web and social media mining › web analytics
web measurement
0.112020
Measuring the Emergence of Consent Management on the Web · Internet Measurement Conference 2020

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

longitudinal measurement · 0.9controlled experiment · 0.9browser crawling · 0.9
YearPublicationVenuePosition
2021 Privacy Preference Signals: Past, Present and Future
abstract
Abstract Privacy preference signals are digital representations of how users want their personal data to be processed. Such signals must be adopted by both the sender (users) and intended recipients (data processors). Adoption represents a coordination problem that remains unsolved despite efforts dating back to the 1990s. Browsers implemented standards like the Platform for Privacy Preferences (P3P) and Do Not Track (DNT), but vendors profiting from personal data faced few incentives to receive and respect the expressed wishes of data subjects. In the wake of recent privacy laws, a coalition of AdTech firms published the Transparency and Consent Framework (TCF), which defines an optin consent signal. This paper integrates post-GDPR developments into the wider history of privacy preference signals. Our main contribution is a high-frequency longitudinal study describing how TCF signal gained dominance as of February 2021. We explore which factors correlate with adoption at the website level. Both the number of third parties on a website and the presence of Google Ads are associated with higher adoption of TCF. Further, we show that vendors acted as early adopters of TCF 2.0 and provide two case-studies describing how Consent Management Providers shifted existing customers to TCF 2.0. We sketch ways forward for a pro-privacy signal.
Maximilian Hils, Daniel W. Woods, Rainer Böhme
Proc. Priv. Enhancing Technol.1
2020 Watching the Weak Link into Your Home: An Inspection and Monitoring Toolkit for TR-069
Maximilian Hils, Rainer Böhme
ACNS (2)1
2020 Measuring the Emergence of Consent Management on the Web
abstract
Privacy laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have pushed internet firms processing personal data to obtain user consent. Uncertainty around sanctions for non-compliance led many websites to embed a Consent Management Provider (CMP), which collects users' consent and shares it with third-party vendors and other websites. Our paper maps the formation of this ecosystem using longitudinal measurements. Primary and secondary data sources are used to measure each actor within the ecosystem. Using 161 million browser crawls, we estimate that CMP adoption doubled from June 2018 to June 2019 and then doubled again until June 2020. Sampling 4.2 million unique domains, we observe that CMP adoption is most prevalent among moderately popular websites (Tranco top 50-10k) but a long tail exists. Using APIs from the ad-tech industry, we quantify the purposes and lawful bases used to justify processing personal data. A controlled experiment on a public website provides novel insights into how the time-to-complete of two leading CMPs' consent dialogues varies with the preferences expressed, showing how privacy aware users incur a significant time cost.
Maximilian Hils, Daniel W. Woods, Rainer Böhme
Internet Measurement Conference1