5 citations · 5 across the 2 of their papers we have counts for
6 papers
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…
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…
Security-by-Design for LLM-Based Code Generation: Leveraging Internal Representations for Concept-Driven Steering Mechanisms
Maximilian Wendlinger, Daniel Kowatsch, Konstantin Böttinger +1
Large Language Models (LLMs) show remarkable capabilities in understanding natural language and generating complex code. However, as practitioners adopt CodeLLMs for increasingly c…
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…
Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning
Maximilian Wendlinger, Kilian Tscharke, Pascal Debus
One of the key obstacles in traditional deep learning is the reduction in model transparency caused by increasingly intricate model functions, which can lead to problems such as ov…
Entangled Threats: A Unified Kill Chain Model for Quantum Machine Learning Security
Pascal Debus, Maximilian Wendlinger, Kilian Tscharke +7
Quantum Machine Learning (QML) systems inherit vulnerabilities from classical machine learning while introducing new attack surfaces rooted in the physical and algorithmic layers o…