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Stjepan Picek

Observed names: Picek, Picek, S., Picek, Stjepan, Picek, Stjepan;, S. Picek
Institutions: Radboud University Nijmegen, University of Zagreb, Radboud University Medical Center, Radboud Institute for Molecular Life Sciences, Faculty of Electrical Engineering and Computing in Zagreb, University of Bergen, Delft University of Technology
Observed institutions: Centre National de la Recherche Scientifique, Radboud University Nijmegen, University of Zagreb, Radboud University Medical Center, IEEE Computer Society, iMinds, Laboratoire Analyse, Géométrie et Applications, STMicroelectronics (France), Radboud Institute for Molecular Life Sciences, IMEC, Ikerlan, Faculty of Electrical Engineering and Computing in Zagreb, MIT Computer Science and Artificial Intelligence Laboratory, University of Bergen, Université Paris 8, Massachusetts Institute of Technology, UCLouvain, Delft University of Technology, KU Leuven
ORCID: 0000-0001-7509-4337
Observed ORCID: 0000-0001-7509-4337
OpenAlex ID: A5024072796
Make Some Noise. Unleashing the Power of Convolutional Neural Networks for Profiled Side-channel Analysis
2019 · Jaehun Kim, Stjepan Picek, et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 290
The Curse of Class Imbalance and Conflicting Metrics with Machine Learning for Side-channel Evaluations
2018 · Stjepan Picek, Annelie Heuser, et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 212
{CSI} {NN}: Reverse Engineering of Neural Network Architectures Through Electromagnetic Side Channel
2019 · Lejla Batina, Shivam Bhasin, et al. · Research Repository (Delft University of Technology) · 191
SoK: Deep Learning-based Physical Side-channel Analysis
2022 · Stjepan Picek, Guilherme Perin, et al. · ACM Computing Surveys · 188
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Reinforcement Learning for Hyperparameter Tuning in Deep Learning-based Side-channel Analysis
2021 · Jorai Rijsdijk, Lichao Wu, et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 145
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On the Performance of Convolutional Neural Networks for Side-Channel Analysis
2018 · Stjepan Picek, Ioannis Petros Samiotis, et al. · Lecture notes in computer science · 128
Side-channel analysis and machine learning: A practical perspective
2017 · Stjepan Picek, Annelie Heuser, et al. · International Joint Conference on Neural Networks (IJCNN) · 107
I Choose You: Automated Hyperparameter Tuning for Deep Learning-Based Side-Channel Analysis
2022 · Lichao Wu, Guilherme Perin, et al. · IEEE Transactions on Emerging Topics in Computing · 103
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Predictive and generative machine learning models for photonic crystals
2018 · Thomas Christensen, Charlotte Loh, et al. · Nanophotonics · 103
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Strength in Numbers: Improving Generalization with Ensembles in Machine Learning-based Profiled Side-channel Analysis
2020 · Guilherme Perin, Łukasz Chmielewski, et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 101
Mind the Portability: A Warriors Guide through Realistic Profiled Side-channel Analysis
2020 · Shivam Bhasin, Anupam Chattopadhyay, et al. · Network and Distributed System Security Symposium · 92
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Remove Some Noise: On Pre-processing of Side-channel Measurements with Autoencoders
2020 · Lichao Wu, Stjepan Picek · IACR Transactions on Cryptographic Hardware and Embedded Systems · 89
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Explainability-based Backdoor Attacks Against Graph Neural Networks
2021 · Jing Xu, Minhui (Jason) Xue, et al. · ACM Workshop on Wireless Security and Machine Learning (WiseML) · 81
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Exploring Feature Selection Scenarios for Deep Learning-based Side-channel Analysis
2022 · Guilherme Perin, Lichao Wu, et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 78
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A Comprehensive Study of Jailbreak Attack versus Defense for Large Language Models
2024 · Zihao Xu, Yi Liu, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · 69
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One Trace Is All It Takes: Machine Learning-Based Side-Channel Attack on EdDSA
2019 · Léo Weissbart, Stjepan Picek, et al. · Lecture notes in computer science · 69
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Cellular automata based S-boxes
2018 · Luca Mariot, Stjepan Picek, et al. · Cryptography and Communications · 69
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Cryptographic Boolean functions: One output, many design criteria
2015 · Stjepan Picek, Domagoj Jakobovic, et al. · Applied Soft Computing · 69
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A New Cost Function for Evolution of S-Boxes
2016 · Stjepan Picek, Marko Cupic, et al. · Evolutionary Computation · 67
Lightweight Ciphers and Their Side-Channel Resilience
2017 · Annelie Heuser, Stjepan Picek, et al. · IEEE Transactions on Computers · 55
The Best of Two Worlds: Deep Learning-assisted Template Attack
2022 · Lichao Wu, Guilherme Perin, et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 54
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Template attack versus Bayes classifier
2017 · Stjepan Picek, Annelie Heuser, et al. · Journal of Cryptographic Engineering · 53
Confused by Confusion: Systematic Evaluation of DPA Resistance of Various S-boxes
2014 · Stjepan Picek, Kostas Papagiannopoulos, et al. · Lecture notes in computer science · 53
Keep it Unsupervised: Horizontal Attacks Meet Deep Learning
2020 · Guilherme Perin, Łukasz Chmielewski, et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 51
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The Curse of Class Imbalance and Conflicting Metrics with Machine Learning for Side-channel Evaluations
2018 · Picek, Stjepan, Heuser, Annelie, et al. · HAL · 50
Works count: 398
Citation count: 5,551
H-index: 38
I10-index: 135
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