Euclidean and Rapid Jacobian-based Saliency Maps Attacks - IEEE Xplore
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Apr 18, 2022 · In this paper, we mainly introduce Euclidean Jacobian-based Saliency Maps Attack(EJSMA) and Rapid Jacobian-based Saliency Maps Attacks(RJSMA).
EJSMA uses the Grad-CAM method to construct a new saliency map, RJSMA aims to reduce the size of the Jacobian matrix and increase the speed of attack. To.
These attacks are improved on the basis of the JSMA, faster and more efficient version of JSMA and greatly improves upon the speed of TJSMA, ...
Sep 20, 2023 · Samples are generated using the Euclidean Jacobian-based Saliency Map Attack (EJSMA) to evaluate classification outcomes using adversarial ...
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Jul 12, 2020 · In this paper, we show that penalising saliency maps of JSMA by the output probabilities and the input features of the NNC allows to obtain more powerful ...
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Apr 16, 2024 · Adversarial examples are inputs to Machine Learning (ML) models that are intentionally designed to fool the model.
In this research, we are using the Jacobian-based Saliency Map Attack (JSMA) algorithm to generate adversarial samples. NSL-KDD dataset is used, which is a ...
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Return to Article Details Adversarial Sample Generation using the Euclidean Jacobian-based Saliency Map Attack (EJSMA) and Classification for IEEE 802.11 using ...
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Aug 23, 2018 · I. INTRODUCTION. The Jacobian-based Saliency Map Attack [1] is a family of adversarial attack methods [2], [3] for fooling classification.
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Jacobian-based Saliency Map Attack (JSMA). Unlike FGSM, the method uses feature selection to minimize the number of features modified while causing ...