GAN-Based Evasion Attack in Filtered Multicarrier Waveforms Systems
IEEE Transactions on Machine Learning in Communications and NetworkingGenerative adversarial networks (GANs), a category of deep learning models, have become a cybersecurity concern for wireless communication systems. These networks enable potential attackers to deceive receivers that rely on convolutional neural networks (
Kawtar Zerhouni +5 more
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Restricted Evasion Attack: Generation of Restricted-Area Adversarial Example
IEEE Access, 2019 Deep neural networks (DNNs) show superior performance in image and speech recognition. However, adversarial examples created by adding a little noise to an original sample can lead to misclassification by a DNN.
Hyun Kwon, Hyunsoo Yoon, Daeseon Choi
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On-Device Smishing Classifier Resistant to Text Evasion Attack
IEEE AccessSmishing (SMS phishing) is a cybercrime in which criminals send fraudulent messages, including malicious links, to steal the victims’ private data or cause financial losses.
Jae Woo Seo +6 more
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FP-ZOO: Fast Patch-Based Zeroth Order Optimization for Black-Box Adversarial Attacks on Vision Models [PDF]
SensorsDeep neural networks have outperformed conventional methods in various fields such as image recognition, natural language processing, and speech recognition.
Junho Seo, Seungho Jeon
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Multi-Targeted Adversarial Example in Evasion Attack on Deep Neural Network
IEEE Access, 2018 Deep neural networks (DNNs) are widely used for image recognition, speech recognition, pattern analysis, and intrusion detection. Recently, the adversarial example attack, in which the input data are only slightly modified, although not an issue for ...
Hyun Kwon +4 more
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MaskDGA: An Evasion Attack Against DGA Classifiers and Adversarial Defenses
IEEE Access, 2020 Domain generation algorithms (DGAs) are commonly used by botnets to generate domain names that bots can use to establish communication channels with their command and control servers.
Lior Sidi, Asaf Nadler, Asaf Shabtai
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Adversarial Evasion Attacks on SVM-Based GPS Spoofing Detection Systems [PDF]
SensorsGPS spoofing remains a critical threat in the use of autonomous vehicles. Machine-learning-based detection systems, particularly support vector machines (SVMs), demonstrate high accuracy in their defense against conventional spoofing attacks.
Sunghyeon An +2 more
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Dual-Targeted adversarial example in evasion attack on graph neural networks [PDF]
Scientific ReportsThis study proposes a novel approach for generating dual-targeted adversarial examples in Graph Neural Networks (GNNs), significantly advancing the field of graph-based adversarial attacks.
Hyun Kwon, Dae-Jin Kim
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AlgorithmsIncorporating Artificial Intelligence (AI) in healthcare has transformed disease diagnosis and treatment by offering unprecedented benefits. However, it has also revealed critical cybersecurity vulnerabilities in Deep Learning (DL) models, which raise ...
Sarfraz Brohi, Qurat-ul-ain Mastoi
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Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attack [PDF]
IEEE International Conference on Computer Vision, 2023 In autonomous driving (AD), accurate perception is indispensable to achieving safe and secure driving. Due to its safety-criticality, the security of AD perception has been widely studied.
Ningfei Wang +4 more
semanticscholar +1 more source