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Benny Rolle

dblp:361/1409 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0002-8961-6962ORCID · 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
Systems and software security · 62% Privacy and data protection · 38%

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

TopicWeightPapersLastEvidence papers
Systems and software security
information flow tracking
0.712023
General Data Protection Runtime: Enforcing Transparent GDPR Compliance for Existing Applications · CCS 2023
Privacy and data protection › privacy compliance
GDPR compliance
0.212023
General Data Protection Runtime: Enforcing Transparent GDPR Compliance for Existing Applications · CCS 2023
Privacy and data protection › privacy policy
privacy policy enforcement
0.212023
General Data Protection Runtime: Enforcing Transparent GDPR Compliance for Existing Applications · CCS 2023

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

metadata labeling · 0.7dynamic information flow tracking · 0.7
YearPublicationVenuePosition
2023 General Data Protection Runtime: Enforcing Transparent GDPR Compliance for Existing Applications
abstract
Recent advances in data protection regulations brings privacy benefits for website users, but also comes at a cost for operators. Retrofitting the privacy requirements of laws such as the General Data Protection Regulation (GDPR) onto legacy software requires significant auditing and development effort. In this work we demonstrate that this effort can be minimized by viewing data protection requirements through the lens of information flow tracking. Instead of manual inspections of applications, we propose a lightweight enforcement engine which can reliably prevent unlawful data processing even in the presence of bugs or misconfigured software. Taking GDPR regulations as a starting point, we define twelve software requirements which, if implemented properly, ensure adequate handling of personal data. We go on to show how these requirements can be fulfilled by proposing a metadata structure and enforcement policies for dynamic information flow tracking frameworks. To put this idea into practice, we present Fontus, a Java Virtual Machine (JVM) information flow tracking framework, which can transparently label personal data in existing Java applications in order to aid compliance with data protection regulations. Finally, we demonstrate the applicability of our approach by enforcing data protection polices across 7 large, open source web applications, with no changes required to the applications themselves.
David Klein 0001, Benny Rolle, Thomas Barber, Manuel Karl, Martin Johns
CCS2