Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies

Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
Total Pages: 83
Release: 2019-08-22
Genre: Computers
ISBN: 0309496098
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The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11â€"12, 2018, in Berkeley, California, to discuss robust machine learning algorithms and systems for the detection and mitigation of adversarial attacks and anomalies. This publication summarizes the presentations and discussions from the workshop.


Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies
Language: en
Pages: 83

Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies

Authors: National Academies of Sciences, Engineering, and Medicine
Categories: Computers
Type: BOOK - Published: 2019-08-22 - Publisher: National Academies Press

GET EBOOK

The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11â€"12, 201
Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies
Language: en
Pages: 83

Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies

Authors: National Academies of Sciences, Engineering, and Medicine
Categories: Computers
Type: BOOK - Published: 2019-08-22 - Publisher: National Academies Press

GET EBOOK

The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11â€"12, 201
Adversarial Machine Learning
Language: en
Pages: 341

Adversarial Machine Learning

Authors: Anthony D. Joseph
Categories: Computers
Type: BOOK - Published: 2019-02-21 - Publisher: Cambridge University Press

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Written by leading researchers, this complete introduction brings together all the theory and tools needed for building robust machine learning in adversarial e
Machine Learning Algorithms
Language: en
Pages: 109

Machine Learning Algorithms

Authors: Fuwei Li
Categories: Computers
Type: BOOK - Published: 2022-11-14 - Publisher: Springer Nature

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This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through presenting the optimal attacks in wireles
Studying the Robustness of Machine Learning-based Malware Detection Models
Language: en
Pages: 0

Studying the Robustness of Machine Learning-based Malware Detection Models

Authors: Ahmed Abusnaina
Categories:
Type: BOOK - Published: 2022 - Publisher:

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With the rise of the popularity of machine learning (ML), it has been shown that ML-based classifiers are susceptible to adversarial examples and concept drifti