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Kevin Eykholt
Kevin Eykholt
Verified email at ibm.com
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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
2121*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
3212018
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
1072017
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
382018
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
382017
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
132018
Robust physical-world attacks on deep learning visual classification
K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, C Xiao, A Prakash, ...
Journal of Environmental Sciences (China) English Ed, 2017
132017
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
62020
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
62017
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
42021
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
42017
Designing adversarially resilient classifiers using resilient feature engineering
K Eykholt, A Prakash
arXiv preprint arXiv:1812.06626, 2018
32018
Adaptive Verifiable Training Using Pairwise Class Similarity
S Wang, K Eykholt, T Lee, J Jang, I Molloy
Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 10201 …, 2021
22021
Robust classification using robust feature augmentation
K Eykholt, S Gupta, A Prakash, A Rahmati, P Vaishnavi, H Zheng
arXiv preprint arXiv:1905.10904, 2019
22019
Constraining neural networks for robustness through alternative encoding
K Eykholt, T Lee, IM Molloy, J Jang
US Patent App. 17/112,628, 2022
12022
Transferring Adversarial Robustness Through Robust Representation Matching
P Vaishnavi, K Eykholt, A Rahmati
arXiv preprint arXiv:2202.09994, 2022
12022
Designing and Evaluating Physical Adversarial Attacks and Defenses for Machine Learning Algorithms
K Eykholt
12019
Transferable Adversarial Robustness using Adversarially Trained Autoencoders.
P Vaishnavi, K Eykholt, A Prakash, A Rahmati
CoRR, 2019
12019
Benchmarking the Effect of Poisoning Defenses on the Security and Bias of the Final Model
NB Angel, K Eykholt, F Ahmed, Y Zhou, S Priya, T Lee, SR Kadhe, M Tan, ...
Annual Conference on Neural Information Processing Systems, 2022
2022
On the Feasibility of Compressing Certifiably Robust Neural Networks
P Vaishnavi, V Krish, F Ahmed, K Eykholt, A Rahmati
Annual Conference on Neural Information Processing Systems, 2022
2022
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