Matt Fredrikson
Cited by
Cited by
The limitations of deep learning in adversarial settings
N Papernot, P McDaniel, S Jha, M Fredrikson, ZB Celik, A Swami
2016 IEEE European symposium on security and privacy (EuroS&P), 372-387, 2016
Model inversion attacks that exploit confidence information and basic countermeasures
M Fredrikson, S Jha, T Ristenpart
Proceedings of the 22nd ACM SIGSAC conference on computer and communications …, 2015
Privacy risk in machine learning: Analyzing the connection to overfitting
S Yeom, I Giacomelli, M Fredrikson, S Jha
2018 IEEE 31st Computer Security Foundations Symposium (CSF), 2018
Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing
M Fredrikson, E Lantz, S Jha, S Lin, D Page, T Ristenpart
USENIX Security Symposium, 17-32, 2014
Universal and transferable adversarial attacks on aligned language models
A Zou, Z Wang, JZ Kolter, M Fredrikson
arXiv preprint arXiv:2307.15043, 2023
Synthesizing near-optimal malware specifications from suspicious behaviors
M Fredrikson, S Jha, M Christodorescu, R Sailer, X Yan
2010 IEEE Symposium on Security and Privacy, 45-60, 2010
Stolen memories: Leveraging model memorization for calibrated {White-Box} membership inference
K Leino, M Fredrikson
29th USENIX security symposium (USENIX Security 20), 1605-1622, 2020
Cyber SA: Situational awareness for cyber defense
P Barford, M Dacier, TG Dietterich, M Fredrikson, J Giffin, S Jajodia, S Jha, ...
Cyber Situational Awareness: Issues and Research, 3-13, 2010
On the Practical Exploitability of Dual EC DRBG in TLS Implementations
S Checkoway, M Fredrikson, R Niederhagen, M Green, T Lange, ...
USENIX Security Symposium, 319-335, 2014
A methodology for formalizing model-inversion attacks
X Wu, M Fredrikson, S Jha, JF Naughton
2016 IEEE 29th computer security foundations symposium (CSF), 355-370, 2016
A layered architecture for detecting malicious behaviors
L Martignoni, E Stinson, M Fredrikson, S Jha, JC Mitchell
International Symposium on Recent Advances in Intrusion Detection, 78-97, 2008
Repriv: Re-imagining content personalization and in-browser privacy
M Fredrikson, B Livshits
2011 IEEE Symposium on Security and Privacy, 131-146, 2011
Verified security for browser extensions
A Guha, M Fredrikson, B Livshits, N Swamy
2011 IEEE symposium on security and privacy, 115-130, 2011
Globally-robust neural networks
K Leino, Z Wang, M Fredrikson
International Conference on Machine Learning, 6212-6222, 2021
Representation engineering: A top-down approach to ai transparency
A Zou, L Phan, S Chen, J Campbell, P Guo, R Ren, A Pan, X Yin, ...
arXiv preprint arXiv:2310.01405, 2023
Fliptest: fairness testing via optimal transport
E Black, S Yeom, M Fredrikson
Proceedings of the 2020 conference on fairness, accountability, and …, 2020
Mining graph patterns efficiently via randomized summaries
C Chen, CX Lin, M Fredrikson, M Christodorescu, X Yan, J Han
Proceedings of the VLDB Endowment 2 (1), 742-753, 2009
Influence-directed explanations for deep convolutional networks
K Leino, S Sen, A Datta, M Fredrikson, L Li
2018 IEEE international test conference (ITC), 1-8, 2018
Proxy non-discrimination in data-driven systems
A Datta, M Fredrikson, G Ko, P Mardziel, S Sen
arXiv preprint arXiv:1707.08120, 2017
Why are they collecting my data? inferring the purposes of network traffic in mobile apps
H Jin, M Liu, K Dodhia, Y Li, G Srivastava, M Fredrikson, Y Agarwal, ...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018
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