Deep neural networks have been shown to be highly vulnerable to adversarial examples-inputs crafted to mislead models by adding subtle, human-imperceptible perturbations. Transferability and stealthiness are two crucial metrics for evaluating adversa...
Biomedical physics & engineering express
Nov 19, 2025
Artificial intelligence (AI) systems are increasingly used in medical imaging for disease diagnosis, yet their vulnerability to adversarial attacks poses significant risks for clinical deployment. In this work, we systematically evaluate the suscepti...
The Internet of Medical Things represents an interconnected medical technology that comprises mobile applications, medical services, as well as networks. These medical equipment and software are connected to medical systems across an internet connect...
People routinely capture photos and videos to document their daily experiences, with such visual media frequently regarded as reliable sources of evidence. The proliferation of social networking platforms, digital photography technologies, and image ...
A denial of service (DoS) attack is an essential and nonstop threat to cybersecurity. Generally, DoS attacks are executed by forcing a victim's computer to reset and consume its sources. Distributed DoS (DDoS) is the most underlined and significant a...
The proliferation of Internet of Medical Things (IoMT) devices has created cybersecurity challenges that requiring advanced threat detection techniques along with preserving patient privacy. This paper introduces FedMedSecure, a federated few-shot le...
As the primary link in cybersecurity, the intrusion detection system (IDS) is of indispensable importance. Many studies have proposed sophisticated artificial intelligence (AI) models to detect intrusion behavior from a large amount of data, yet they...
Federated learning (FL) has become more popular in the area of machine learning for protecting data privacy, its unique distributed data processing characteristics have garnered widespread attention. However, the implementation of FL faces many chall...
The rapid evolution of cyber threats poses significant challenges to the adaptability and performance of anomaly detection systems. This study presents an innovative hybrid deep learning framework that integrates Convolutional Neural Networks (CNN), ...
Diabetic retinopathy (DR) is a major problemfor the diabetes patients that makes a serious threat to vision and causes the irreversible blindness if not diagnosed and treated early. Conventional deep learning-based approaches designed for DR detectio...
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