Universal Adversarial Training Using Auxiliary Conditional Generative Model-Based Adversarial Attack Generation

Universal Adversarial Training Using Auxiliary Conditional Generative Model-Based Adversarial Attack Generation

While Machine Learning has become the holy grail of modern-day computing, it has many security flaws that have yet to be addressed and resolved. Adversarial attacks are one of these security flaws, in which an attacker appends noise to data samples that machine learning models take as input with the...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Hiskias Dingeto, Juntae Kim
Format: Artikel
Sprache:English
Veröffentlicht: MDPI AG 2023-07-01
Schriftenreihe:Applied Sciences
Schlagworte:
adversarial training
adversarial attacks
generative models
conditional generative adversarial network
auxiliary conditional generative adversarial networks
Online Zugang:https://www.mdpi.com/2076-3417/13/15/8830

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https://www.mdpi.com/2076-3417/13/15/8830

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