Machine Learning

Voltage Fault Injection Against On-Device Language Models
Transformer-based language models are increasingly deployed on resource-constrained edge devices, raising new security concerns when …
Oct 31, 2026 12:40 PM 2026 International Workshop on Hardware and Architectural Support for Security and Privacy (HASP 2026)
Anthony Etim, Jakub Szefer
Power Side-Channel Attacks on Machine-Learning-based Quantum Error Correction Decoders
Machine-learning (ML) decoders are increasingly used in quantum error correction (QEC) to process measured syndromes and determine …
Oct 31, 2026 12:30 PM 2026 International Workshop on Hardware and Architectural Support for Security and Privacy (HASP 2026)
Anthony Etim, Jakub Szefer
Fault Attacks on ML-based Quantum Control and Error Correction
Machine-learning (ML) models are increasingly used in quantum computing systems to discriminate multi-qubit readouts, mitigate …
Sep 14, 2026 2:00 PM 2026 IEEE International Conference on Quantum Computing and Engineering (QCE 2026)
Anthony Etim, Jakub Szefer
Fault Injection Attacks and Countermeasures on TinyML Algorithms
TinyML algorithms, designed to operate on constrained devices such as those found in Internet of Things (IoT) systems, are vulnerable …
Anthony Etim, Srilalith Nampally, Aubtin Rasouli, Dustin Mazza, Krishna Chilakapati, Tinghung Chiu, Ferhat Erata, Leyla Nazhandali, Wenjie Xiong, Jakub Szefer
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Power Side-Channel Attacks on Machine-Learning-based Quantum Error Correction Decoders
Machine learning (ML) decoders are increasingly used in quantum error correction (QEC) to model noise, analyze imperfect syndrome …
Anthony Etim, Jakub Szefer
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Fault Attacks on ML-based Quantum Control and Error Correction
Machine-learning (ML) models are increasingly used in quantum computing systems to discriminate multi-qubit readouts, mitigate …
Anthony Etim, Jakub Szefer
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