Countering Evasion Attacks for Smart Grid Reinforcement Learning-Based Detectors
IEEE Access, 2023 Fraudulent customers in smart power grids employ cyber-attacks by manipulating their smart meters and reporting false consumption readings to reduce their bills.
Ahmed T. El-Toukhy +4 more
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An Evasion Attack against Stacked Capsule Autoencoder [PDF]
Algorithms, 2022 Capsule networks are a type of neural network that use the spatial relationship between features to classify images. By capturing the poses and relative positions between features, this network is better able to recognize affine transformation and ...
Jiazhu Dai, Siwei Xiong
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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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AlphaFold reveals how pathogenic Leptospira use cross-kingdom thiol-disulfide exchange to evade the complement membrane attack complex [PDF]
mBioLeptospirosis is a globally significant severe infectious disease that affects a range of mammals. To understand its complex aetiopathogenesis, Leptospira spp.
Abbie Hinds +8 more
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Adversarial attacks against supervised machine learning based network intrusion detection systems
PLoS ONE, 2022 Adversarial machine learning is a recent area of study that explores both adversarial attack strategy and detection systems of adversarial attacks, which are inputs specially crafted to outwit the classification of detection systems or disrupt the ...
Ebtihaj Alshahrani +3 more
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Kernel-based adversarial attacks and defenses on support vector classification
Digital Communications and Networks, 2022 While malicious samples are widely found in many application fields of machine learning, suitable countermeasures have been investigated in the field of adversarial machine learning. Due to the importance and popularity of Support Vector Machines (SVMs),
Wanman Li +3 more
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Microbiology Spectrum, 2023 Plasmodium parasites are the etiological agents of malaria, a disease responsible for over half a million deaths annually. Successful completion of the parasite’s life cycle in the vertebrate host and transmission to a mosquito vector is contingent upon ...
Medard Ernest +7 more
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Gradient Masking of Label Smoothing in Adversarial Robustness
IEEE Access, 2021 Deep neural networks (DNNs) have achieved impressive results in several image classification tasks. However, these architectures are unstable for adversarial examples (AEs) such as inputs crafted by a hardly perceptible perturbation with the intent of ...
Hyungyu Lee, Ho Bae, Sungroh Yoon
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A Feasibility Study on Evasion Attacks Against NLP-Based Macro Malware Detection Algorithms
IEEE Access, 2023 Machine learning-based models for malware detection have gained prominence in order to detect obfuscated malware. These models extract malicious features and endeavor to classify samples as either malware or benign entities.
Mamoru Mimura, Risa Yamamoto
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Optimized Adversarial Example With Classification Score Pattern Vulnerability Removed
IEEE Access, 2022 Neural networks provide excellent service on recognition tasks such as image recognition and speech recognition as well as for pattern analysis and other tasks in fields related to artificial intelligence.
Hyun Kwon, Kyoungmin Ko, Sunghwan Kim
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