WordRevert: Adversarial Examples Defence Method for Chinese Text Classification
IEEE Access, 2022 Adversarial examples can evade the detection of text classification models based on Deep Neural Networks (DNNs), thus posing a potential security threat to the system.
Enhui Xu +5 more
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Adversarial Attack for SAR Target Recognition Based on UNet-Generative Adversarial Network
Remote Sensing, 2021 Some recent articles have revealed that synthetic aperture radar automatic target recognition (SAR-ATR) models based on deep learning are vulnerable to the attacks of adversarial examples and cause security problems.
Chuan Du, Lei Zhang
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Defending Against Adversarial Attacks On Medical Imaging Ai System, Classification Or Detection? [PDF]
IEEE International Symposium on Biomedical Imaging, 2020 Medical imaging AI systems such as disease classification and segmentation are increasingly inspired and transformed from computer vision based AI systems. Although an array of defense techniques have been developed and proved to be effective in computer
X. Li, Deng Pan, D. Zhu
semanticscholar +1 more source
Synthesis of the common-law accusatorial and the continental mixed criminal procedural justice system: The example of the International Criminal Tribunal for the Former Yugoslavia: Part 1. [PDF]
Pravni Zapisi, 2014 In this paper, the author analyses criminal procedural rules created as an expression of the synthesis of the common-law accusatorial and the continental mixed criminal procedural justice system in International Tribunal for Former Yugoslavia (ICTY). The
Radulović Jovan
doaj
Cybersecurity, 2020 Deep learning (DL) has exhibited its exceptional performance in fields like intrusion detection. Various augmentation methods have been proposed to improve data quality and eventually to enhance the performance of DL models.
Yixiang Wang +4 more
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A System-Driven Taxonomy of Attacks and Defenses in Adversarial Machine Learning
IEEE Transactions on Emerging Topics in Computational Intelligence, 2020 Machine Learning (ML) algorithms, specifically supervised learning, are widely used in modern real-world applications, which utilize Computational Intelligence (CI) as their core technology, such as autonomous vehicles, assistive robots, and biometric ...
Koosha Sadeghi +2 more
semanticscholar +1 more source
Synthesis of the common-law accusatorial and the continental mixed criminal procedural justice system: The example of the International Criminal Tribunal for the Former Yugoslavia: Part 2. [PDF]
Pravni Zapisi, 2014 In this paper, the author analyses criminal procedural rules created as an expression of the synthesis of the common-law accusatorial and the continental mixed criminal procedural justice system in International Tribunal for Former Yugoslavia (ICTY). The
Radulović Jovan
doaj
GANG-MAM: GAN based enGine for Modifying Android Malware
SoftwareX, 2022 Malware detectors based on machine learning are vulnerable to adversarial attacks. Generative Adversarial Networks (GAN) are architectures based on Neural Networks that may be used to produce successful adversarial samples.
Renjith G. +4 more
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Exploring Diverse Feature Extractions for Adversarial Audio Detection
IEEE Access, 2023 Although deep learning models have exhibited excellent performance in various domains, recent studies have discovered that they are highly vulnerable to adversarial attacks.
Yujin Choi +3 more
doaj +1 more source
Applied SciencesIndustrial control systems (ICSs) are critical components automating the processes and operations of electromechanical systems. These systems are vulnerable to cyberattacks and can be the targets of malicious activities.
Hayriye Tanyıldız +2 more
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