The Impact of Simultaneous Adversarial Attacks on Robustness of Medical Image Analysis
Deep learning models are widely used in healthcare systems. However, deep learning
models are vulnerable to attacks themselves. Significantly, due to the black-box nature of the …
models are vulnerable to attacks themselves. Significantly, due to the black-box nature of the …
DFDAN: A Dual-branch Feature Decoupling-driven Auxiliary Network for Enhanced Fault Diagnosis Safety
J Zhao, N Li - IEEE Transactions on Instrumentation and …, 2024 - ieeexplore.ieee.org
The widespread use of machine learning models in fault diagnosis introduces vulnerabilities
to adversarial attacks, which can compromise equipment operation and pose significant …
to adversarial attacks, which can compromise equipment operation and pose significant …
Hybrid Intrusion Detection System for IoT Against Adversarial Threats Using Intelligent RDLS Model
The Internet of Things (IoT) has revolutionized smart city solutions, enhancing operational
efficiency and user convenience. Nonetheless, the integration of deep learning (DL) models …
efficiency and user convenience. Nonetheless, the integration of deep learning (DL) models …