| Robust physical-world attacks on deep learning visual classification K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, C Xiao, A Prakash, ... Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 3382* | 2018 |
| Physical adversarial examples for object detectors D Song, K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, F Tramer, ... 12th USENIX workshop on offensive technologies (WOOT 18), 2018 | 585 | 2018 |
| Internet of things security research: A rehash of old ideas or new intellectual challenges? E Fernandes, A Rahmati, K Eykholt, A Prakash IEEE Security & Privacy 15 (4), 79-84, 2017 | 136 | 2017 |
| Note on attacking object detectors with adversarial stickers K Eykholt, I Evtimov, E Fernandes, B Li, D Song, T Kohno, A Rahmati, ... arXiv preprint arXiv:1712.08062, 2017 | 48 | 2017 |
| Tyche: A risk-based permission model for smart homes A Rahmati, E Fernandes, K Eykholt, A Prakash 2018 IEEE Cybersecurity Development (SecDev), 29-36, 2018 | 41 | 2018 |
| Robust physical-world attacks on deep learning models (2017) K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, C Xiao, A Prakash, ... arXiv preprint arXiv:1707.08945, 2018 | 23 | 2018 |
| Robust physical-world attacks on deep learning visual classification K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, C Xiao, A Prakash, ... | 22 | 2020 |
| Tyche: Risk-based permissions for smart home platforms A Rahmati, E Fernandes, K Eykholt, A Prakash arXiv preprint arXiv:1801.04609, 2018 | 15 | 2018 |
| Transferring adversarial robustness through robust representation matching P Vaishnavi, K Eykholt, A Rahmati 31st USENIX Security Symposium (USENIX Security 22), 2083-2098, 2022 | 13 | 2022 |
| Separation of powers in federated learning (poster paper) PC Cheng, K Eykholt, Z Gu, H Jamjoom, KR Jayaram, E Valdez, A Verma Proceedings of the First Workshop on Systems Challenges in Reliable and …, 2021 | 13 | 2021 |
| EdgeTorrent: Real-time Temporal Graph Representations for Intrusion Detection IJ King, X Shu, J Jang, K Eykholt, T Lee, HH Huang Proceedings of the 26th International Symposium on Research in Attacks …, 2023 | 10 | 2023 |
| Can attention masks improve adversarial robustness? P Vaishnavi, T Cong, K Eykholt, A Prakash, A Rahmati International Workshop on Engineering Dependable and Secure Machine Learning …, 2020 | 10 | 2020 |
| Accelerating certified robustness training via knowledge transfer P Vaishnavi, K Eykholt, A Rahmati Advances in Neural Information Processing Systems 35, 5269-5281, 2022 | 9 | 2022 |
| Ares: A system-oriented wargame framework for adversarial ml F Ahmed, P Vaishnavi, K Eykholt, A Rahmati 2022 IEEE Security and Privacy Workshops (SPW), 73-79, 2022 | 7 | 2022 |
| Heimdall: A privacy-respecting implicit preference collection framework A Rahmati, E Fernandes, K Eykholt, X Chen, A Prakash Proceedings of the 15th Annual International Conference on Mobile Systems …, 2017 | 7 | 2017 |
| Ensuring Authorized Updates in Multi-user {Database-Backed} Applications K Eykholt, A Prakash, B Mozafari 26th USENIX Security Symposium (USENIX Security 17), 1445-1462, 2017 | 6 | 2017 |
| {URET}: Universal Robustness Evaluation Toolkit (for Evasion) K Eykholt, T Lee, D Schales, J Jang, I Molloy 32nd USENIX Security Symposium (USENIX Security 23), 3817-3833, 2023 | 5 | 2023 |
| DeTA: Minimizing Data Leaks in Federated Learning via Decentralized and Trustworthy Aggregation PC Cheng, K Eykholt, Z Gu, H Jamjoom, KR Jayaram, E Valdez, A Verma Proceedings of the Nineteenth European Conference on Computer Systems, 219-235, 2024 | 4 | 2024 |
| Constraining neural networks for robustness through alternative encoding K Eykholt, T Lee, IM Molloy, J Jang US Patent 11,847,555, 2023 | 3 | 2023 |
| Graph neural network (gnn) training using meta-path neighbor sampling and contrastive learning D She, X Shu, K Eykholt, J Jang US Patent App. 17/480,012, 2023 | 3 | 2023 |
