Intrusion detection in IoT systems using denoising autoencoder
Protection against unwanted intrusions is crucial for preserving the integrity and security of
connected devices in the context of Internet of Things (IoT) networks. The growing number of …
connected devices in the context of Internet of Things (IoT) networks. The growing number of …
Research on adaptive 1DCNN network intrusion detection technology based on BSGM mixed sampling
The development of internet technology has brought us benefits, but at the same time, there
has been a surge in network attack incidents, posing a serious threat to network security. In …
has been a surge in network attack incidents, posing a serious threat to network security. In …
On TinyML and Cybersecurity: Electric Vehicle Charging Infrastructure Use Case
As technology advances, the use of Machine Learning (ML) in cybersecurity is becoming
increasingly crucial to tackle the growing complexity of cyber threats. While traditional ML …
increasingly crucial to tackle the growing complexity of cyber threats. While traditional ML …
[PDF][PDF] Anomaly Network Intrusion Detection System based on Hybrid Feature Selection Method
MSS Moe, WM Oo - researchgate.net
The current increase in hackings and computer network attacks around the world has make
stronger the need to develop better intrusion detection and prevention systems for …
stronger the need to develop better intrusion detection and prevention systems for …