5 citations
6 papers
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…
Architecture-Derived CBOMs for Cryptographic Migration: A Security-Aware Architecture Tradeoff Method
Eduard Hirsch, Kristina Raab
Cryptographic migration driven by algorithm deprecation, regulatory change, and post-quantum readiness requires more than an inventory of cryptographic assets. Existing Cryptograph…
Detecting Cryptographically Relevant Software Packages with Collaborative LLMs
Eduard Hirsch, Kristina Raab, Tobias J. Bauer +1
IT systems are facing an increasing number of security threats, including advanced persistent attacks and future quantum-computing vulnerabilities. The move towards crypto-agility…
Influence of Parallelism in Vector-Multiplication Units on Correlation Power Analysis
Manuel Brosch, Matthias Probst, Stefan Kögler +1
The use of neural networks in edge devices is increasing, which introduces new security challenges related to the neural networks' confidentiality. As edge devices often offer phys…
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…
GPTrace: Effective Crash Deduplication Using LLM Embeddings
Patrick Herter, Vincent Ahlrichs, Ridvan Açilan +1
Fuzzing is a highly effective method for uncovering software vulnerabilities, but analyzing the resulting data typically requires substantial manual effort. This is amplified by th…