A data-driven cyber–physical system using deep-learning convolutional neural networks: Study on false-data injection attacks in an unmanned ground vehicle under …
Leveraging the benefits of deep-learning convolutional neural networks, we introduce a new
data-driven cyber–physical system specifically designed to address the vulnerability of …
data-driven cyber–physical system specifically designed to address the vulnerability of …
Real-time anomaly detection using hardware-based unsupervised spiking neural network (tinysnn)
We present TinySNN, a novel unsupervised spiking neural network hardware designed for
real-time anomaly detection. TinySNN provides an energy-efficient edge computing solution …
real-time anomaly detection. TinySNN provides an energy-efficient edge computing solution …
[Retracted] A Deep Spiking Neural Network Anomaly Detection Method
L Hu, Y Liu, W Qiu - Computational Intelligence and …, 2022 - Wiley Online Library
Cyber‐attacks on specialized industrial control systems are increasing in frequency and
sophistication, which means stronger countermeasures need to be implemented, requiring …
sophistication, which means stronger countermeasures need to be implemented, requiring …