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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… 
2019
2019
Intelligent Systems Design for Malware Classification Under Adversarial Conditions
The use of machine learning and intelligent systems has become an established practice in the realm of malware detection and… 
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
Fishy Faces: Crafting Adversarial Images to Poison Face Authentication
Face recognition systems are becoming a prevalent authentication solution on smartphones. This work is the first to deploy a… 
Review
2018
Review
2018
Classical Machine Learning and Its Applications to IDS
This chapter provides a brief preliminary study regarding classical machine learning which consists of six different models… 
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… 
2017
2017
Attacking Machine Learning models as part of a cyber kill chain
Machine learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as… 
2007
2007
Foundations of Adversarial Machine Learning
As classifiers are deployed to detect malicious behavior ran ging from spam to terrorism, adversaries modify their behaviors to… 
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