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Defense strategies for Adversarial Machine Learning: A survey
Computer Science Review, 2023Panagiotis Bountakas +3 more
semanticscholar +1 more source
A state-of-the-art review on adversarial machine learning in image classification
Multimedia tools and applications, 2023Ashish Bajaj, D. Vishwakarma
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SoK: Explainable Machine Learning in Adversarial Environments
IEEE Symposium on Security and PrivacyModern deep learning methods have long been considered black boxes due to the lack of insights into their decision-making process. However, recent advances in explainable machine learning have turned the tables.
Maximilian Noppel, Christian Wressnegger
semanticscholar +1 more source
Adversarial Attacks in Machine Learning: Key Insights and Defense Approaches
Applied Data Science and AnalysisThere is a considerable threat present in genres such as machine learning due to adversarial attacks which include purposely feeding the system with data that will alter the decision region.
Yahya Layth Khaleel +2 more
semanticscholar +1 more source
Poltergeist: Acoustic Adversarial Machine Learning against Cameras and Computer Vision
IEEE Symposium on Security and Privacy, 2021Xiaoyu Ji +6 more
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Adversarial Machine Learning in Wireless Communications Using RF Data: A Review
IEEE Communications Surveys and Tutorials, 2023Damilola Adesina +2 more
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A Survey on Generative Adversarial Networks: Variants, Applications, and Training
ACM Computing Surveys, 2022Songyuan Li
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Generative Adversarial Networks in Time Series: A Systematic Literature Review
ACM Computing Surveys, 2023Eoin Brophy, Zhengwei Wang, Qi She
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