Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Privacy in Neural Network Learning: Threats and Countermeasures
Deep Learning with Differential Privacy
LOGAN: Evaluating Privacy Leakage of Generative Models Using Generative Adversarial Networks
Neural Network Approach to Web Application Protection
Security and Privacy in m-Learning and Beyond : Challenges and State-ofthe-art Georgios Kambourakis Laboratory of Information and Communications Systems Security
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification
Limiting privacy breaches in privacy preserving data mining
On the Design and Analysis of the Privacy-Preserving SVM Classifier
SecureML: A System for Scalable Privacy-Preserving Machine Learning
Privacy-preserving Machine Learning through Data Obfuscation
Learning a Secure Classifier against Evasion Attack
Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences
Learning Adversary-Resistant Deep Neural Networks
Learning to Transfer Privileged Information
State-of-the-art in privacy preserving data mining
Revealing information while preserving privacy
Detecting adversarial example attacks to deep neural networks
Privacy Skyline: Privacy with Multidimensional Adversarial Knowledge
Differentially Private Bayesian Learning on Distributed Data
Data Poisoning Attacks against Online Learning
Biologically inspired protection of deep networks from adversarial attacks
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Proximate Time-Optimal Digital Control for Synchronous Buck DC–DC Converters
Gaussian Processes for Machine Learning
Intelligent Personal Assistant with Knowledge Navigation
PeerFlow: Secure Load Balancing in Tor