adversarial examples
adversarial-examples-85f05ac4·3 events·first seen 28d agoAliases: adversarial examples
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Robust Adversarial Inputs: Multi-Scale Fooling of Neural Network Classifiers
OpenAI researchers created adversarial images that reliably fool neural network classifiers even when viewed from varied scales and perspectives. This directly challenges the assumption that self-driving car vision systems are robust to adversarial attacks due to their multi-angle image capture. The finding has implications for the security of deployed vision systems in safety-critical applications.
Attacking Machine Learning with Adversarial Examples
This 2017 OpenAI blog post introduces adversarial examples — inputs intentionally crafted to cause machine learning models to make mistakes, analogized to optical illusions for machines. It surveys how adversarial examples manifest across different input modalities and discusses the fundamental difficulties in defending against them. The post is an early foundational explainer on adversarial robustness from OpenAI.
Adversarial Attacks on Neural Network Policies
OpenAI published research examining adversarial attacks on neural network-based reinforcement learning policies. The work investigates how small, carefully crafted perturbations to observations can cause trained RL agents to fail catastrophically. This represents an early investigation into the robustness and safety of learned policies under adversarial conditions.