Results 41 to 50 of about 7,737 (292)
Adversarial Attack and Defense: A Survey
, 2022 In recent years, artificial intelligence technology represented by deep learning has achieved remarkable results in image recognition, semantic analysis, natural language processing and other fields.
Hongshuo Liang +4 more
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Scaling provable adversarial defenses
CoRR, 2018 Recent work has developed methods for learning deep network classifiers that are provably robust to norm-bounded adversarial perturbation; however, these methods are currently only possible for relatively small feedforward networks. In this paper, in an effort to scale these approaches to substantially larger models, we extend previous work in three ...
Eric Wong 0001 +3 more
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Stylized Pairing for Robust Adversarial Defense
, 2022 Recent studies show that deep neural networks (DNNs)-based object recognition algorithms overly rely on object textures rather than global object shapes, and DNNs are also vulnerable to human-less perceptible adversarial perturbations. Based on these two
Xiao Liu, Wentao Zhao, Dejian Guan
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Adversarial Attacks and Defenses in Deep Learning
Engineering, 2020 With the rapid developments of artificial intelligence (AI) and deep learning (DL) techniques, it is critical to ensure the security and robustness of the deployed algorithms.
Kui Ren +3 more
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Text Adversarial Purification as Defense against Adversarial Attacks
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023 Accepted by ACL2023 main ...
Linyang Li, Demin Song, Xipeng Qiu
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Big Data and Cognitive Computing, 2020 In this work, we propose a novel defense system against adversarial examples leveraging the unique power of Generative Adversarial Networks (GANs) to generate new adversarial examples for model retraining. To do so, we develop an automated pipeline using
Shayan Taheri +3 more
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Sparsity based defense against adversarial examples: v1.0
, 2020 Sparsity-based defense against adversarial attacks on machine learning classifiers. Contains code for the following papers: S. Gopalakrishnan, Z. Marzi, U. Madhow, R.
Soorya Gopalakrishnan
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Remote Sensing, 2023 Deep neural networks (DNNs) have been widely utilized in automatic visual navigation and recognition on modern unmanned aerial vehicles (UAVs), achieving state-of-the-art performances.
Zihao Lu, Hao Sun, Yanjie Xu
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Defending Against Adversarial Attacks with Camera Image Pipelines
, 2023 Existing neural networks for computer vision tasks are vulnerable to adversarial attacks: adding imperceptible perturbations to the input images can fool these models into making a false prediction on an image that was correctly predicted without the ...
Zhang, Yuxuan
core
An Empirical Review of Adversarial Defenses
CoRR, 2020 19 pages, 8 Figures, Report Reviewed by Vivek ...
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