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Adversarial machine learning

Adversarial machine learning is a research field that lies at the intersection of machine learning and computer security. It aims to enable the safe… 
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Related topics

Related topics

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BiometricsInternational Conference on Machine LearningJournal of Machine Learning ResearchTensorFlow

Broader (2)

Computer securityMachine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2020
Review
2020
Adversarial Machine Learning for Text
In this tutorial, we investigate the history, evolution and latest research topics in the area of adversarial machine learning… 
2020
2020
An Adversarial Approach for Explaining the Predictions of Deep Neural Networks
Machine learning models have been successfully applied to a wide range of applications including computer vision, natural… 
2019
2019
Adversarial Attacks on Grid Events Classification: An Adversarial Machine Learning Approach
With the ever-increasing reliance on data for data-driven applications in power grids, such as event cause analysis, the… 
2019
2019
Legislating Autonomous Vehicles against the Backdrop of Adversarial Machine Learning Findings
Recent studies on adversarial machine learning1 made Michael Grossman, a Texas-based injury lawyer, skeptical of the viability of… 
2019
2019
Adversarial Machine Learning with Double Oracle
We aim to improve the general adversarial machine learning solution by introducing the double oracle idea from game theory, which… 
2018
2018
A Compact Reconfigurable Multi-mode Resonator-based Multi-band Band Pass Filter for Intelligent Transportation Systems Applications
A compact wide band reconfigurable bandpass filter (BPF) which utilises a hemi-circular flower shaped multimode resonator (MMR… 
2018
2018
Intrusion-Resilient Classifier Approximation: From Wildcard Matching to Range Membership
We study the problem of securing machine learning classifiers against intrusion attacks (i.e., attacks that somehow retrieve the… 
2018
2018
Adversarial Evasion-Resilient Hardware Malware Detectors
Machine learning offers tantalizing possibilities in computing and autonomous systems: data driven components and systems are… 
2017
2017
Deep encrypted text categorization
Long short-term memory (LSTM) is a significant approach to capture the long-range temporal context in sequences of arbitrary… 
2016
2016
Securing pervasive systems against adversarial machine learning
Applications and middleware in pervasive systems frequently rely on machine learning to provide adaptivity and customization that… 
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