We are attending a severe zero-day cyber attacks. Machine learning based anomaly
detection is definitely the most efficient defence in depth approach. It consists to analyzing …

The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …

As computer networks and interconnected systems continue to gain widespread adoption,
ensuring cybersecurity has become a prominent concern for organizations, regardless of …

Recently, federated learning has been used by Network Intrusion Detection Systems
(NIDSs) to expanding data features while preserving data privacy. However, non …

With the increase and diversity of network attacks, machine learning has shown its efficiency
in realizing intrusion detection. Federated Learning (FL) has been proposed as a new …

Because of the complexity of network traffic, there are various significant challenges in the
network anomaly detection fields. One of the major challenges is the lack of labeled training …

Machine learning has helped advance the field of anomaly detection by incorporating
classifiers and autoencoders to decipher between normal and anomalous behaviour …

Intrusion detection is a common network security defense technology. At present, there are
many research using deep learning to realize network intrusion detection. This method has …

Cyberattacks are a major issues and it causes organizations great financial, and reputation
harm. However, due to various factors, the current network intrusion detection systems …

Federated learning is the new tide that is being associated with machine learning territory. It
is an attempt to enable smart edge devices to confederate a mutual prediction model while …