dr. S. Picek (Stjepan)

• Matteo Cardaioli, Stefano Cecconello, Mauro Conti, and Simone Milani, Stjepan Picek, Eugen Saraci: Hand Me Your PIN! Inferring ATM PINs of Users Typing with a Covered Hand. USENIX Security Symposium 2022 Volledige tekst
• Shivam Bhasin, Anupam Chattopadhyay, Annelie Heuser, Dirmanto Jap, Stjepan Picek, Ritu Ranjan Shrivastwa. Mind the Portability: A Warriors Guide through Realistic Profiled Side-channel Analysis. NDSS 2020. Volledige tekst
• Lejla Batina, Shivam Bhasin, Dirmanto Jap, Stjepan Picek. CSI NN: Reverse Engineering of Neural Network Architectures Through Electromagnetic Side Channel. USENIX Security Symposium 2019: 515-532. Volledige tekst
• Stjepan Picek, Annelie Heuser, Alan Jovic, Shivam Bhasin, Francesco Regazzoni: The Curse of Class Imbalance and Conflicting Metrics with Machine Learning for Side-channel Evaluations. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2019(1): 209-237 (2019) Volledige tekst
• Jaehun Kim, Stjepan Picek, Annelie Heuser, Shivam Bhasin, Alan Hanjalic: Make Some Noise. Unleashing the Power of Convolutional Neural Networks for Profiled Side-channel Analysis. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2019(3): 148-179 (2019) Volledige tekst

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H-index: 28

• 2019 - Best paper award: Walter Krawec, Stjepan Picek, Domagoj Jakobovic: Evolutionary Algorithms for the Design of Quantum Protocols. International Conference on the Applications of Evolutionary Computation (Part of EvoStar) Meer informatie

• 2015 - 2018 Evolutionary computation algorithms represent a range of problem-solving techniques based on principles of biological evolution, like natural selection and genetic inheritance. Such algorithms can be used to solve a variety of difficult problems, among which are those from the area of cryptography. Examples of such an approach include the evolving hash functions or creation of a new block cipher. First results in this area have emerged over 30 years ago, and in recent years there has been an increased interest in this area. Still, some problems like problem formulation and representation remain open. This project deals with various applications of optimization and learning with evolutionary computation in cryptography. The project is fully funded by the Croatian science foundation under the contract IP-2014-09-4882. Meer informatie
• 2021 - 2024 Chipkaarten zoals transport- of bankkaarten zijn gewilde doelwitten voor aanvallers die hiervoor vaak gebruik maken van zijkanalen. Dit voorstel zal de kracht van zulke aanvallers in schatten met behulp van machine learning algoritmen teneinde deze toestellen, en onze data in het algemeen, te beschermen met de gepaste tegenmaatregelen. Meer informatie
• 2021 - 2025 Modern society is interconnected through electronic and mobile devices, which we call the Internet of Things (IoT). The lack of proper protection mechanisms can lead to privacy violations and financial loss. The goal of PROACT is to design novel algorithms and silicon chips with inherent protection against physical attacks, and to develop novel simulation and evaluation techniques for physical security. PROACT will therefore contribute to an increased protection of our personal and company-critical data.

• Bachelor Thesis
• Master Thesis Computing Science
• Master Thesis Information Sciences
• Networks and Security
• Research Internship
• Security and Privacy of Machine Learning

• Assistant professor, TU Delft (01 oktober 2021 - 30 september 2025)
  https://www.tudelft.nl/ewi