Privacy

CAUDIT: Continuous Auditing of SSH Servers To Mitigate Brute-Force Attacks NSDI 2019 Characterizing the Sample Complexity of Pure Private Learners JMLR 2019 Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters ICML 2019 Content Authentication for Neural Imaging Pipelines: End-To-End Optimization of Photo Provenance in Complex Distribution Channels CVPR 2019 Data-Anonymous Encoding for Text-to-SQL Generation EMNLP 2019 Data Poisoning against Differentially-Private Learners: Attacks and Defenses IJCAI 2019 Deanonymizing Social Networks Using Structural Information IJCAI 2019 Deep Leakage from Gradients NeurIPS 2019 Deep Reinforcement Learning-based Text Anonymization against Private-Attribute Inference EMNLP 2019 Defending Neural Backdoors via Generative Distribution Modeling NeurIPS 2019 Deniable Upload and Download via Passive Participation NSDI 2019 Differentially Private Algorithms for Learning Mixtures of Separated Gaussians NeurIPS 2019 Differentially Private Anonymized Histograms NeurIPS 2019 Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate NeurIPS 2019 Differentially Private Bayesian Linear Regression NeurIPS 2019 Differentially Private Community Detection in Attributed Social Networks ACML 2019 Differentially Private Covariance Estimation NeurIPS 2019 Differentially Private Distributed Data Summarization under Covariate Shift NeurIPS 2019 Differentially Private Empirical Risk Minimization with Non-convex Loss Functions ICML 2019 Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View AAAI 2019 Differentially Private Fair Learning ICML 2019 Differentially Private Iterative Gradient Hard Thresholding for Sparse Learning IJCAI 2019 Differentially Private Learning of Geometric Concepts ICML 2019 Differentially Private Markov Chain Monte Carlo NeurIPS 2019 Differentially Private Online Submodular Minimization AISTATS 2019