Stefanos Koffas, Stjepan Picek, Mauro Conti (2022), Dynamic Backdoors with Global Average Pooling, In Proceedings of the 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS) p.320-323, IEEE .

Guilherme Perin, Lichao Wu, Stjepan Picek (2022), Exploring Feature Selection Scenarios for Deep Learning-based Side-channel Analysis, In IACR Transactions on Cryptographic Hardware and Embedded Systems Volume 2022 p.828-861.

Naila Mukhtar, Lejla Batina, Stjepan Picek, Yinan Kong (2022), Fake It Till You Make It: Data Augmentation Using Generative Adversarial Networks for All the Crypto You Need on Small Devices, Steven D. Galbraith (Eds.), In Topics in Cryptology - CT-RSA 2022 p.297-321, Springer.

Maikel Kerkhof, Lichao Wu, Guilherme Perin, Stjepan Picek (2022), Focus is Key to Success: A Focal Loss Function for Deep Learning-Based Side-Channel Analysis, Josep Balasch, Colin O’Flynn (Eds.), In Constructive Side-Channel Analysis and Secure Design - 13th International Workshop, COSADE 2022, Proceedings Volume 13211 p.29-48, Springer.

Guilherme Perin, Lichao Wu, Stjepan Picek (2022), Gambling for Success: The Lottery Ticket Hypothesis in Deep Learning-Based Side-Channel Analysis, M. Stamp (Eds.), In Advances in Information Security p.217-241, Springer Nature.

Yier Jin, Tsung Yi Ho, Stjepan Picek, Siddharth Garg (2022), Guest Editorial: Trustworthy AI, ACM Journal on Emerging Technologies in Computing Systems Volume 18.

Matteo Cardaioli, Stefano Cecconello, Mauro Conti, Simone Milani, Stjepan Picek, Eugen Saraci (2022), Hand Me Your PIN! Inferring ATM PINs of Users Typing with a Covered Hand, In Proceedings of the 31st USENIX Security Symposium, Security 2022 p.1687-1704, USENIX Association.

Lichao Wu, Guilherme Perin, Stjepan Picek (2022), I Choose You: Automated Hyperparameter Tuning for Deep Learning-based Side-channel Analysis, In IEEE Transactions on Emerging Topics in Computing p.1-12.

M. Conti, Jiaxin Li, S. Picek, J. Xu (2022), Label-Only Membership Inference Attack against \\Node-Level Graph Neural Networks, In AISec 2022 - Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security, co-located with CCS 2022 p.1–12, Association for Computing Machinery (ACM).

J. Xu, R. Wang, S. Koffas, K. Liang, S. Picek (2022), More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks, In Proceedings - 38th Annual Computer Security Applications Conference, ACSAC 2022 p.684–698, Association for Computing Machinery (ACM).