activity
20112026
most citedPrivacy Risk Assessment: From Art to Science, By Metrics

32 citations · 48 across the 12 of their papers we have counts for

collaborators

12 papers

cs.MA2026

Multi-Agent Cooperative Learning for Robust Vision-Language Alignment under OOD Concepts

Philip Xu

This paper introduces a novel Multi-Agent Cooperative Learning (MACL) framework to address cross-modal alignment collapse in vision-language models when handling out-of-distributio…

cs.LG2025

Privacy-Preserving Generative Models: A Comprehensive Survey

Debalina Padariya, Isabel Wagner, Aboozar Taherkhani +1

Despite the generative model's groundbreaking success, the need to study its implications for privacy and utility becomes more urgent. Although many studies have demonstrated the p…

cs.CY2023

What's going on at the back-end? Risks and benefits of smart toilets

Isabel Wagner, Eerke Boiten

This paper presents a thematic analysis of an expert focus group considering smart toilets that record health data. The themes that arise indicate risks, many of which could be mit…

cs.CR2023

Changes in Conducting Data Protection Risk Assessment and After GDPR implementation

Fatemeh Zarrabi, Isabel Wagner, Eerke Boiten

Based on Article 35 of the EU (European Union) General Data Protection Regulation, a Data Protection Impact Assessment (DPIA) is necessary whenever there is a possibility of a high…

cs.CR2022★ 4 cited

Systematic Literature Review: Anti-Phishing Defences and Their Application to Before-the-click Phishing Email Detection

Trevor Wood, Vitor Basto-Fernandes, Eerke Boiten +1

Most research into anti-phishing defence assumes that the mal-actor is attempting to harvest end-users' personally identifiable information or login credentials and, hence, focuses…

cs.CR2017★ 32 cited

Privacy Risk Assessment: From Art to Science, By Metrics

Isabel Wagner, Eerke Boiten

Privacy risk assessments aim to analyze and quantify the privacy risks associated with new systems. As such, they are critically important in ensuring that adequate privacy protect…