collaborators

10 papers

quant-ph2026

A Multiclass Quantum Aligned Centroid Kernel

Kilian Tscharke, Pascal Debus

Kernel methods are powerful tools in machine learning but commonly used full-Gram kernels face three key limitations: (1) quadratic scaling with training set size; (2) the use of f…

quant-ph2026

An End-to-End Multi-Stage Kill-Chain Attack on Quantum Neural Networks: Demonstration on Trapped-Ion Hardware

Cedric Brügmann, Daniel Herr, Daniel Ohl de Mello +7

We demonstrate an end-to-end, multi-stage attack against a quantum neural network (QNN) model that is executed on a trapped-ion quantum computer. Our chain combines side-channel re…

cs.SD2026

The Watermark Shortcut: How Provenance Marking Sabotages Audio Deepfake Detection

Nicolas M. Müller, Nicolas M. Müller, Pascal Debus

Provenance watermarking is increasingly treated as a safeguard for synthetic speech, whether built directly into speech-generation models such as Chatterbox, provided through dedic…

quant-ph2026

Quantum Autoencoder for Multivariate Time Series Anomaly Detection

Kilian Tscharke, Maximilian Wendlinger, Afrae Ahouzi +4

Anomaly Detection (AD) defines the task of identifying observations or events that deviate from typical - or normal - patterns, a critical capability in IT security for recognizing…

quant-ph2025

Quantum Support Vector Regression for Robust Anomaly Detection

Kilian Tscharke, Maximilian Wendlinger, Sebastian Issel +1

Anomaly Detection (AD) is critical in data analysis, particularly within the domain of IT security. In this study, we explore the potential of Quantum Machine Learning for applicat…

quant-ph2025

Quantum Machine Learning Playground

Pascal Debus, Sebastian Issel, Kilian Tscharke

This article introduces an innovative interactive visualization tool designed to demystify quantum machine learning (QML) algorithms. Our work is inspired by the success of classic…