Adversarial_Attack_using_Neural_Image_Modification - Jan 17.pdf (12.45 MB)
Download fileAdversarial Attack using Neural Image Modification
In order to help development into analyzing the characteristics of adversarial sample generation in artificial neural networks, this work proposes a framework for an adversarial attack that utilizes neural image modification to generate an adversarial sample. This method proves to be effective in reducing a target network’s accuracy in both untargeted
and targeted attacks with good success rates. This method also shows some effectiveness against defensive
distillation, but not transferrable between multiple models.
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Email Address of Submitting Author
jandrikrlana@gmail.comORCID of Submitting Author
0000-0001-7819-566XSubmitting Author's Institution
Quezon City Science High SchoolSubmitting Author's Country
- Philippines