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20212023
most citedExploring the Privacy Risks of Adversarial VR Game Design

47 citations · 110 across the 11 of their papers we have counts for

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Showing 2022 · cs.CRShow all

5 papers · 2 filters

cs.CR2022★ 4 cited

Lessons Learned: Surveying the Practicality of Differential Privacy in the Industry

Gonzalo Munilla Garrido, Xiaoyuan Liu, Florian Matthes +1

Since its introduction in 2006, differential privacy has emerged as a predominant statistical tool for quantifying data privacy in academic works. Yet despite the plethora of resea…

cs.CR2022★ 9 cited

Exploring privacy-enhancing technologies in the automotive value chain

Gonzalo Munilla Garrido, Kaja Schmidt, Christopher Harth-Kitzerow +3

Privacy-enhancing technologies (PETs) are becoming increasingly crucial for addressing customer needs, security, privacy (e.g., enhancing anonymity and confidentiality), and regula…

cs.CR2022★ 47 cited

Exploring the Privacy Risks of Adversarial VR Game Design

Vivek Nair, Gonzalo Munilla Garrido, Dawn Song +1

Fifty study participants playtested an innocent-looking "escape room" game in virtual reality (VR). Within just a few minutes, an adversarial program had accurately inferred over 2…

cs.CR2022

Verifying Outsourced Computation in an Edge Computing Marketplace

Christopher Harth-Kitzerow, Gonzalo Munilla Garrido

An edge computing marketplace could enable IoT devices (Outsourcers) to outsource computation to any participating node (Contractors) in their proximity. In return, these nodes rec…

cs.CR2022

Exponential Randomized Response: Boosting Utility in Differentially Private Selection

Gonzalo Munilla Garrido, Florian Matthes

A differentially private selection algorithm outputs from a finite set the item that approximately maximizes a data-dependent quality function. The most widely adopted mechanisms t…