Benjamin I. P. Rubinstein
Benjamin I. P. Rubinstein
Professor, School of Computing and Information Systems, The University of Melbourne
Verified email at - Homepage
Cited by
Cited by
Adversarial machine learning
L Huang, AD Joseph, B Nelson, BIP Rubinstein, JD Tygar
Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence …, 2011
ANTIDOTE: Understanding and defending against poisoning of anomaly detectors
BIP Rubinstein, B Nelson, L Huang, AD Joseph, S Lau, S Rao, N Taft, ...
Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement …, 2009
Exploiting Machine Learning to Subvert Your Spam Filter.
B Nelson, M Barreno, FJ Chi, AD Joseph, BIP Rubinstein, U Saini, ...
First USENIX Workshop on Large-scale Exploits and Emergent Threats (LEET'08 …, 2008
A Bayesian approach to discovering truth from conflicting sources for data integration
B Zhao, BIP Rubinstein, J Gemmell, J Han
Proceedings of the VLDB Endowment 5 (6), 550-561, 2012
Learning in a large function space: Privacy-preserving mechanisms for SVM learning
BIP Rubinstein, PL Bartlett, L Huang, N Taft
Journal of Privacy and Confidentiality 4 (1), 65-100, 2012
Identifying At-Risk Students in Massive Open Online Courses
J He, J Bailey, BIP Rubinstein, R Zhang
Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI …, 2015
PPFA: Privacy preserving fog-enabled aggregation in smart grid
L Lyu, K Nandakumar, B Rubinstein, J Jin, J Bedo, M Palaniswami
IEEE Transactions on Industrial Informatics 14 (8), 3733-3744, 2018
Link prediction by de-anonymization: How we won the kaggle social network challenge
A Narayanan, E Shi, BIP Rubinstein
The 2011 International Joint Conference on Neural Networks (IJCNN), 1825-1834, 2011
Machine-learning algorithms predict graft failure after liver transplantation
L Lau, Y Kankanige, B Rubinstein, R Jones, C Christophi, V Muralidharan, ...
Transplantation 101 (4), e125-e132, 2017
Misleading learners: Co-opting your spam filter
B Nelson, M Barreno, FJ Chi, AD Joseph, BIP Rubinstein, U Saini, ...
Machine Learning in Cyber Trust, 17-51, 2009
Security evaluation of support vector machines in adversarial environments
B Biggio, I Corona, B Nelson, BIP Rubinstein, D Maiorca, G Fumera, ...
Support vector machines applications, 105-153, 2014
Query Strategies for Evading Convex-Inducing Classifiers.
B Nelson, BIP Rubinstein, L Huang, AD Joseph, SJ Lee, S Rao, JD Tygar
Journal of Machine Learning Research 13 (5), 2012
Robust and private Bayesian inference
C Dimitrakakis, B Nelson, A Mitrokotsa, BIP Rubinstein
Algorithmic Learning Theory: 25th International Conference, ALT 2014, Bled …, 2014
Adaptive bidding for display advertising
A Ghosh, BIP Rubinstein, S Vassilvitskii, M Zinkevich
Proceedings of the 18th International Conference on World Wide Web, 251-260, 2009
On the differential privacy of Bayesian inference
Z Zhang, B Rubinstein, C Dimitrakakis
Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI …, 2016
Adversarial Machine Learning
AD Joseph, B Nelson, BIP Rubinstein, JD Tygar
Cambridge University Press, 2019
Health data in an open world
C Culnane, BIP Rubinstein, V Teague
arXiv preprint arXiv:1712.05627, 2017
A game theoretical approach to defend against co-resident attacks in cloud computing: Preventing co-residence using semi-supervised learning
Y Han, T Alpcan, J Chan, C Leckie, BIP Rubinstein
IEEE Transactions on information Forensics and Security 11 (3), 556-570, 2015
Evolving quantum circuits using genetic programming
BIP Rubinstein
Proceedings of the 2001 Congress on Evolutionary Computation, 144-151, 2001
Reinforcement learning for autonomous defence in software-defined networking
Y Han, BIP Rubinstein, T Abraham, T Alpcan, O De Vel, S Erfani, ...
Decision and Game Theory for Security: 9th International Conference, GameSec …, 2018
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