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Prateek Mittal
Prateek Mittal
Verified email at princeton.edu - Homepage
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Cited by
Cited by
Year
Advances and open problems in federated learning
P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ...
Foundations and trends® in machine learning 14 (1–2), 1-210, 2021
49872021
Analyzing federated learning through an adversarial lens
AN Bhagoji, S Chakraborty, P Mittal, S Calo
International Conference on Machine Learning, 634-643, 2019
10412019
Sybilinfer: Detecting sybil nodes using social networks.
G Danezis, P Mittal
Ndss 9, 1-15, 2009
6202009
EASiER: Encryption-based access control in social networks with efficient revocation
S Jahid, P Mittal, N Borisov
Proceedings of the 6th ACM Symposium on Information, Computer and …, 2011
5932011
Robustbench: a standardized adversarial robustness benchmark
F Croce, M Andriushchenko, V Sehwag, E Debenedetti, N Flammarion, ...
arXiv preprint arXiv:2010.09670, 2020
5212020
Rocking drones with intentional sound noise on gyroscopic sensors
Y Son, H Shin, D Kim, Y Park, J Noh, K Choi, J Choi, Y Kim
24th USENIX Security Symposium (USENIX Security 15), 881-896, 2015
4262015
Rocking drones with intentional sound noise on gyroscopic sensors
Y Son, H Shin, D Kim, Y Park, J Noh, K Choi, J Choi, Y Kim
24th USENIX Security Symposium (USENIX Security 15), 881-896, 2015
4262015
{BlackIoT}:{IoT} botnet of high wattage devices can disrupt the power grid
S Soltan, P Mittal, HV Poor
27th USENIX Security Symposium (USENIX Security 18), 15-32, 2018
3782018
{BotGrep}: Finding {P2P} Bots with Structured Graph Analysis
S Nagaraja, P Mittal, CY Hong, M Caesar, N Borisov
19th USENIX Security Symposium (USENIX Security 10), 2010
3392010
Ssd: A unified framework for self-supervised outlier detection
V Sehwag, M Chiang, P Mittal
arXiv preprint arXiv:2103.12051, 2021
2722021
{RAPTOR}: Routing attacks on privacy in tor
Y Sun, A Edmundson, L Vanbever, O Li, J Rexford, M Chiang, P Mittal
24th USENIX Security Symposium (USENIX Security 15), 271-286, 2015
2722015
Systematic evaluation of privacy risks of machine learning models
L Song, P Mittal
30th USENIX Security Symposium (USENIX Security 21), 2615-2632, 2021
2682021
Darts: Deceiving autonomous cars with toxic signs
C Sitawarin, AN Bhagoji, A Mosenia, M Chiang, P Mittal
arXiv preprint arXiv:1802.06430, 2018
2672018
Evolution of social-attribute networks: measurements, modeling, and implications using google+
NZ Gong, W Xu, L Huang, P Mittal, E Stefanov, V Sekar, D Song
Proceedings of the 2012 internet measurement conference, 131-144, 2012
2652012
Dependence makes you vulnberable: Differential privacy under dependent tuples.
C Liu, S Chakraborty, P Mittal
NDSS 16, 21-24, 2016
2532016
Denial of service or denial of security?
N Borisov, G Danezis, P Mittal, P Tabriz
Proceedings of the 14th ACM conference on Computer and communications …, 2007
2452007
Enhancing robustness of machine learning systems via data transformations
AN Bhagoji, D Cullina, C Sitawarin, P Mittal
2018 52nd Annual Conference on Information Sciences and Systems (CISS), 1-5, 2018
2292018
Privacy risks of securing machine learning models against adversarial examples
L Song, R Shokri, P Mittal
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …, 2019
2282019
Falcon: Honest-majority maliciously secure framework for private deep learning
S Wagh, S Tople, F Benhamouda, E Kushilevitz, P Mittal, T Rabin
arXiv preprint arXiv:2004.02229, 2020
2242020
Sybilbelief: A semi-supervised learning approach for structure-based sybil detection
NZ Gong, M Frank, P Mittal
IEEE transactions on information forensics and security 9 (6), 976-987, 2014
2162014
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Articles 1–20