Search Results for author: Warren He

Found 9 papers, 5 papers with code

Characterizing Attacks on Deep Reinforcement Learning

no code implementations21 Jul 2019 Chaowei Xiao, Xinlei Pan, Warren He, Jian Peng, Ming-Jie Sun, Jin-Feng Yi, Mingyan Liu, Bo Li, Dawn Song

In addition to current observation based attacks against DRL, we propose the first targeted attacks based on action space and environment dynamics.

Autonomous Driving

Practical Black-box Attacks on Deep Neural Networks using Efficient Query Mechanisms

no code implementations ECCV 2018 Arjun Nitin Bhagoji, Warren He, Bo Li, Dawn Song

An iterative variant of our attack achieves close to 100% attack success rates for both targeted and untargeted attacks on DNNs.

Spatially Transformed Adversarial Examples

3 code implementations ICLR 2018 Chaowei Xiao, Jun-Yan Zhu, Bo Li, Warren He, Mingyan Liu, Dawn Song

Perturbations generated through spatial transformation could result in large $\mathcal{L}_p$ distance measures, but our extensive experiments show that such spatially transformed adversarial examples are perceptually realistic and more difficult to defend against with existing defense systems.

Decision Boundary Analysis of Adversarial Examples

1 code implementation ICLR 2018 Warren He, Bo Li, Dawn Song

We find that the boundaries around these adversarial examples do not resemble the boundaries around benign examples.

Exploring the Space of Black-box Attacks on Deep Neural Networks

1 code implementation ICLR 2018 Arjun Nitin Bhagoji, Warren He, Bo Li, Dawn Song

An iterative variant of our attack achieves close to 100% adversarial success rates for both targeted and untargeted attacks on DNNs.

Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong

no code implementations15 Jun 2017 Warren He, James Wei, Xinyun Chen, Nicholas Carlini, Dawn Song

We ask whether a strong defense can be created by combining multiple (possibly weak) defenses.

Proof of Luck: an Efficient Blockchain Consensus Protocol

1 code implementation16 Mar 2017 Mitar Milutinovic, Warren He, Howard Wu, Maxinder Kanwal

In the paper, we present designs for multiple blockchain consensus primitives and a novel blockchain system, all based on the use of trusted execution environments (TEEs), such as Intel SGX-enabled CPUs.

Cryptography and Security Distributed, Parallel, and Cluster Computing

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