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Patrick McDaniel
Patrick McDaniel
Tsun-Ming Shih Professor of Computer Sciences, University of Wisconsin-Madison
Verified email at cs.wisc.edu - Homepage
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Cited by
Cited by
Year
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
51432016
Taintdroid: an information-flow tracking system for realtime privacy monitoring on smartphones
W Enck, P Gilbert, S Han, V Tendulkar, BG Chun, LP Cox, J Jung, ...
ACM Transactions on Computer Systems (TOCS) 32 (2), 1-29, 2014
51202014
Practical black-box attacks against machine learning
N Papernot, P McDaniel, I Goodfellow, S Jha, ZB Celik, A Swami
Proceedings of the 2017 ACM on Asia conference on computer and …, 2017
44082017
Distillation as a defense to adversarial perturbations against deep neural networks
N Papernot, P McDaniel, X Wu, S Jha, A Swami
2016 IEEE symposium on security and privacy (SP), 582-597, 2016
39542016
Ensemble adversarial training: Attacks and defenses
F Tramèr, A Kurakin, N Papernot, I Goodfellow, D Boneh, P McDaniel
arXiv preprint arXiv:1705.07204, 2017
34302017
Flowdroid: Precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for android apps
S Arzt, S Rasthofer, C Fritz, E Bodden, A Bartel, J Klein, Y Le Traon, ...
ACM sigplan notices 49 (6), 259-269, 2014
27692014
Transferability in machine learning: from phenomena to black-box attacks using adversarial samples
N Papernot, P McDaniel, I Goodfellow
arXiv preprint arXiv:1605.07277, 2016
21222016
Security and privacy challenges in the smart grid
P McDaniel, S McLaughlin
IEEE security & privacy 7 (3), 75-77, 2009
15872009
On lightweight mobile phone application certification
W Enck, M Ongtang, P McDaniel
Proceedings of the 16th ACM conference on Computer and communications …, 2009
14892009
A study of android application security.
W Enck, D Octeau, PD McDaniel, S Chaudhuri
USENIX security symposium 2 (2), 2011
14032011
Understanding android security
W Enck, M Ongtang, P McDaniel
IEEE security & privacy 7 (1), 50-57, 2009
9912009
On the (statistical) detection of adversarial examples
K Grosse, P Manoharan, N Papernot, M Backes, P McDaniel
arXiv preprint arXiv:1702.06280, 2017
9172017
Secure attribute-based systems
M Pirretti, P Traynor, P McDaniel, B Waters
Proceedings of the 13th ACM conference on Computer and communications …, 2006
8352006
Iccta: Detecting inter-component privacy leaks in android apps
L Li, A Bartel, TF Bissyandé, J Klein, Y Le Traon, S Arzt, S Rasthofer, ...
2015 IEEE/ACM 37th IEEE International Conference on Software Engineering 1 …, 2015
8122015
Semantically rich application‐centric security in Android
M Ongtang, S McLaughlin, W Enck, P McDaniel
Security and Communication Networks 5 (6), 658-673, 2012
7792012
Adversarial examples for malware detection
K Grosse, N Papernot, P Manoharan, M Backes, P McDaniel
Computer Security–ESORICS 2017: 22nd European Symposium on Research in …, 2017
7172017
The space of transferable adversarial examples
F Tramèr, N Papernot, I Goodfellow, D Boneh, P McDaniel
arXiv preprint arXiv:1704.03453, 2017
6732017
Towards the science of security and privacy in machine learning
N Papernot, P McDaniel, A Sinha, M Wellman
arXiv preprint arXiv:1611.03814, 2016
6482016
Sok: Security and privacy in machine learning
N Papernot, P McDaniel, A Sinha, MP Wellman
2018 IEEE European symposium on security and privacy (EuroS&P), 399-414, 2018
6412018
Deep k-nearest neighbors: Towards confident, interpretable and robust deep learning
N Papernot, P McDaniel
arXiv preprint arXiv:1803.04765, 2018
6192018
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