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Yigitcan Kaya
Yigitcan Kaya
Postdoc at UC Santa Barbara
Подтвержден адрес электронной почты в домене ucsb.edu - Главная страница
Название
Процитировано
Процитировано
Год
When does machine learning {FAIL}? generalized transferability for evasion and poisoning attacks
O Suciu, R Marginean, Y Kaya, H Daume III, T Dumitras
27th USENIX Security Symposium (USENIX Security 18), 1299-1316, 2018
3552018
Shallow-Deep Networks: Understanding and Mitigating Network Overthinking
Y Kaya, S Hong, T Dumitras
International Conference on Machine Learning, 3301-3310, 2019
3462019
Terminal Brain Damage: Exposing the Graceless Degradation in Deep Neural Networks Under Hardware Fault Attacks
S Hong, P Frigo, Y Kaya, C Giuffrida, T Dumitraş
28th USENIX Security Symposium (USENIX Security 19), 497-514, 2019
2472019
On the effectiveness of mitigating data poisoning attacks with gradient shaping
S Hong, V Chandrasekaran, Y Kaya, T Dumitraş, N Papernot
arXiv preprint arXiv:2002.11497, 2020
1552020
Security analysis of deep neural networks operating in the presence of cache side-channel attacks
S Hong, M Davinroy, Y Kaya, SN Locke, I Rackow, K Kulda, ...
arXiv preprint arXiv:1810.03487, 2018
1012018
When does data augmentation help with membership inference attacks?
Y Kaya, T Dumitras
International conference on machine learning, 5345-5355, 2021
782021
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
S Hong, Y Kaya, IV Modoranu, T Dumitras
International Conference on Learning Representations 2021, 2021
762021
How to 0wn NAS in your spare time
S Hong, M Davinroy, Y Kaya, D Dachman-Soled, T Dumitraş
International Conference on Learning Representations 2020, 2020
442020
On the effectiveness of regularization against membership inference attacks
Y Kaya, S Hong, T Dumitras
arXiv preprint arXiv:2006.05336, 2020
372020
Qu-anti-zation: Exploiting quantization artifacts for achieving adversarial outcomes
S Hong, MA Panaitescu-Liess, Y Kaya, T Dumitras
Advances in Neural Information Processing Systems 34, 9303-9316, 2021
202021
Demystifying behavior-based malware detection at endpoints
Y Kaya, Y Chen, S Saha, F Pierazzi, L Cavallaro, D Wagner, T Dumitras
arXiv preprint arXiv:2405.06124, 2024
52024
Generating distributional adversarial examples to evade statistical detectors
Y Kaya, B Zafar, S Aydore, N Rauschmayr, K Kenthapadi
52022
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
S Saha, W Wang, Y Kaya, S Feizi, T Dumitras
The Twelfth International Conference on Learning Representations (ICLR 2024), 2024
32024
Understanding, Uncovering, and Mitigating the Causes of Inference Slowdown for Language Models
K Varma, A Numanoğlu, Y Kaya, T Dumitraş
2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 723-740, 2024
12024
The Limitations of Deep Learning Methods in Realistic Adversarial Settings
Y Kaya
12023
Like Oil and Water: Group Robustness Methods and Poisoning Defenses Don’t Mix
MA Panaitescu-Liess, Y Kaya, S Zhu, F Huang, T Dumitras
The Twelfth International Conference on Learning Representations, 2024
2024
Too Big to FAIL: What You Need to Know Before Attacking a Machine Learning System
T Dumitraş, Y Kaya, R Mărginean, O Suciu
Security Protocols XXVI: 26th International Workshop, Cambridge, UK, March …, 2018
2018
PoisonedParrot: Subtle Data Poisoning Attacks to Elicit Copyright-Infringing Content from Large Language Models
MA Panaitescu-Liess, P Pathmanathan, Y Kaya, Z Che, B An, S Zhu, ...
Neurips Safe Generative AI Workshop 2024, 0
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