Can you hear it? backdoor attacks via ultrasonic triggers S Koffas, J Xu, M Conti, S Picek Proceedings of the 2022 ACM Workshop on Wireless Security and Machine …, 2022 | 46 | 2022 |
More is better (mostly): On the backdoor attacks in federated graph neural networks J Xu, R Wang, S Koffas, K Liang, S Picek arXiv preprint arXiv:2202.03195, 2022 | 18 | 2022 |
Watermarking Graph Neural Networks based on Backdoor Attacks J Xu, S Koffas, O Ersoy, S Picek arXiv preprint arXiv:2110.11024, 2021 | 17 | 2021 |
Going in style: Audio backdoors through stylistic transformations S Koffas, L Pajola, S Picek, M Conti ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 16 | 2023 |
Dynamic Backdoors with Global Average Pooling S Koffas, S Picek, M Conti 2022 IEEE 4th International Conference on Artificial Intelligence Circuits …, 2022 | 8 | 2022 |
Towards stealthy backdoor attacks against speech recognition via elements of sound H Cai, P Zhang, H Dong, Y Xiao, S Koffas, Y Li arXiv preprint arXiv:2307.08208, 2023 | 4 | 2023 |
SoK: A Systematic Evaluation of Backdoor Trigger Characteristics in Image Classification G Abad, J Xu, S Koffas, B Tajalli, S Picek, M Conti arXiv preprint arXiv:2302.01740, 2023 | 4 | 2023 |
On the effect of clock frequency on voltage and electromagnetic fault injection S Koffas, PK Vadnala International Conference on Applied Cryptography and Network Security, 127-145, 2022 | 2 | 2022 |
A systematic evaluation of backdoor attacks in various domains S Koffas, B Tajalli, J Xu, M Conti, S Picek Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Use …, 2023 | 1 | 2023 |
BlindSage: Label Inference Attacks against Node-level Vertical Federated Graph Neural Networks M Arazzi, M Conti, S Koffas, M Krcek, A Nocera, S Picek, J Xu arXiv preprint arXiv:2308.02465, 2023 | 1 | 2023 |
Backdoor Pony: Evaluating backdoor attacks and defenses in different domains A Mercier, N Smolin, O Sihlovec, S Koffas, S Picek SoftwareX 22, 101387, 2023 | 1 | 2023 |
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning M Arazzi, S Koffas, A Nocera, S Picek arXiv preprint arXiv:2404.19420, 2024 | | 2024 |
The SpongeNet Attack: Sponge Weight Poisoning of Deep Neural Networks J Lintelo, S Koffas, S Picek arXiv preprint arXiv:2402.06357, 2024 | | 2024 |
Dr. Jekyll and Mr. Hyde: Two Faces of LLMs M Gioele Collu, T Janssen-Groesbeek, S Koffas, M Conti, S Picek arXiv e-prints, arXiv: 2312.03853, 2023 | | 2023 |
Tabdoor: Backdoor Vulnerabilities in Transformer-based Neural Networks for Tabular Data B Pleiter, B Tajalli, S Koffas, G Abad, J Xu, M Larson, S Picek arXiv preprint arXiv:2311.07550, 2023 | | 2023 |
Invisible Threats: Backdoor Attack in OCR Systems M Conti, N Farronato, S Koffas, L Pajola, S Picek arXiv preprint arXiv:2310.08259, 2023 | | 2023 |
Backdoor attack on deep neural networks using inaudible triggers J van der Horst, S Picek, S Koffas, G Acar | | 2023 |
Unveiling the Threat: Investigating Distributed and Centralized Backdoor Attacks in Federated Graph Neural Networks J Xu, S Koffas, S Picek Digital Threats: Research and Practice, 2023 | | 2023 |
Backdoor Attacks in Neural Networks S Koffas Delft Uninversity of Technology, 2021 | | 2021 |