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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

6 relations
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 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… 
2018
2018
Towards Adversarial Configurations for Software Product Lines
Ensuring that all supposedly valid configurations of a software product line (SPL) lead to well-formed and acceptable products is… 
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… 
Review
2017
Review
2017
An Introduction to Adversarial Machine Learning
Machine learning based system are increasingly being used for sensitive tasks such as security surveillance, guiding autonomous… 
2017
2017
An Adversarial Machine Learning Model Against Android Malware Evasion Attacks
With explosive growth of Android malware and due to its damage to smart phone users, the detection of Android malware is one of… 
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