activity
19982023
most citedQuantum-Secure Authentication with a Classical Key

225 citations · 338 across the 30 of their papers we have counts for

collaborators
Showing cs.CRShow all

15 papers · 1 filter

cs.CR2022★ 3 cited

Clones of the Unclonable: Nanoduplicating Optical PUFs and Applications

E. Marakis, U. Rührmair, M. Lachner +3

Physical unclonable functions (PUFs), physical objects that are practically unclonable because of their andom and uncontrollable manufacturing variations, are becoming increasingly…

cs.CR2020★ 5 cited

Data Sanitisation Protocols for the Privacy Funnel with Differential Privacy Guarantees

Milan Lopuhaä-Zwakenberg, Haochen Tong, Boris Škorić

In the Open Data approach, governments and other public organisations want to share their datasets with the public, for accountability and to support participation. Data must be op…

cs.CR2020

The Blob: provable incompressibility and traceability in the whitebox model

Boris Skoric, Wil Michiels

We introduce a scheme for distributing and storing software with cryptographic functionality in the whitebox attacker model. Our scheme satisfies two relevant properties: incompres…

cs.CR2019★ 6 cited

Estimating Numerical Distributions under Local Differential Privacy

Zitao Li, Tianhao Wang, Milan Lopuhaä-Zwakenberg +2

When collecting information, local differential privacy (LDP) relieves the concern of privacy leakage from users' perspective, as user's private information is randomized before se…

cs.CR2019

Improving Frequency Estimation under Local Differential Privacy

Milan Lopuhaä-Zwakenberg, Zitao Li, Boris Škorić +1

Local Differential Privacy protocols are stochastic protocols used in data aggregation when individual users do not trust the data aggregator with their private data. In such proto…

cs.CR2019★ 14 cited

Information-theoretic metrics for Local Differential Privacy protocols

Milan Lopuhaä-Zwakenberg, Boris Škorić, Ninghui Li

Local Differential Privacy (LDP) protocols allow an aggregator to obtain population statistics about sensitive data of a userbase, while protecting the privacy of the individual us…