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Adversarial example detection by predicting adversarial noise in the frequency domain
Recent advances in deep neural network (DNN) techniques have increased the importance of security and robustness of algorithms where DNNs are...
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Adversarial example generation for object detection using a data augmentation framework and momentum
Object detection plays a vital role in numerous fields, including unmanned vehicles, security, and industry, among others. However, recent studies...
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Adversarial Example Detection with Latent Representation Dynamic Prototype
In the realm of Deep Neural Networks (DNNs), one of the primary concerns is their vulnerability in adversarial environments, whereby malicious...
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Attribute-guided face adversarial example generation
Deep neural networks (DNNs) are susceptible to adversarial examples generally generated by adding imperceptible perturbations to the clean images,...
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Adversarial attack detection framework based on optimized weighted conditional stepwise adversarial network
Artificial Intelligence (AI)-based IDS systems are susceptible to adversarial attacks and face challenges such as complex evaluation methods,...
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Adversarial example detection based on saliency map features
In recent years, machine learning has greatly improved image recognition capability. However, studies have shown that neural network models are...
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Revisiting model’s uncertainty and confidences for adversarial example detection
Security-sensitive applications that rely on Deep Neural Networks (DNNs) are vulnerable to small perturbations that are crafted to generate...
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Semi-supervised lung nodule detection with adversarial learning
Lung cancer has long posed a severe threat to human life and health, and early detection as well as effective treatment can significantly improve the...
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FD-GAN: Generalizable and Robust Forgery Detection via Generative Adversarial Networks
Generalization across various forgeries and robustness against corruption are pressing challenges of forgery detection. Although previous works boost...
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A non-global disturbance targeted adversarial example algorithm combined with C&W and Grad-Cam
Adversarial examples are artificially crafted to mislead deep learning systems into making wrong decisions. In the research of attack algorithms...
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A low-frequency adversarial attack method for object detection using generative model
Object detection is widely employed in security-critical scenarios. With the rapid development of deep learning, deep learning-based object detection...
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Adversarial Example Attacks and Defenses in DNS Data Exfiltration
The Domain Network System (DNS) protocol is used on a daily basis to access the internet. It acts as a phone book that allows users to access...
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Clustering-based attack detection for adversarial reinforcement learning
Detecting malicious attacks presents a major challenge in the field of reinforcement learning (RL), as such attacks can force the victim to perform...
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X-Detect: explainable adversarial patch detection for object detectors in retail
Object detection models, which are widely used in various domains (such as retail), have been shown to be vulnerable to adversarial attacks. Existing...
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Graph-based domain adversarial learning framework for video anomaly detection domain generalization
The limited domain generalization capability of contemporary video anomaly detection methods restricts their efficacy to specific datasets. To...
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Detection of adversarial attacks based on differences in image entropy
Although deep neural networks (DNNs) have achieved high performance across various applications, they are often deceived by adversarial examples...
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Unveiling vulnerabilities: evading YOLOv5 object detection through adversarial perturbations and steganography
In the realm of machine learning, a discernible surge in research has been observed, focusing on the development of adversarial perturbations with...
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An adversarial pedestrian detection model based on virtual fisheye image training
Fisheye camera is an important sensor in on-board systems and surveillance systems. However, the current fisheye image pedestrian detection still...
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Cycle map** with adversarial event classification network for fake news detection
In recent years, there is a increase in researchers’ interest on social evidence, particularly for fake news detection (FND). However, news posts on...
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A two-stage adversarial Transformer based approach for multivariate industrial time series anomaly detection
Sensors in complex industrial systems generate multivariate time series data, frequently leading to diverse abnormal patterns that pose challenges...
