The rapid advances in the internet and communication fields have resulted in a huge increase in the network size and the corresponding data. As a result, many novel attacks are …
Recent developments in maintenance modelling fueled by data-based approaches such as machine learning (ML), have enabled a broad range of applications. In the automotive …
The increasing trend toward using the Internet of Things (IoT) increased the number of intrusions and intruders annually. Hence, the integration, confidentiality, and access to …
Pervasive growth and usage of the Internet and mobile applications have expanded cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
The increase in internet usage brings security problems with it. Malicious software can affect the operation of the systems and disrupt data confidentiality due to the security gaps in the …
To protect the network, resources, and sensitive data, the intrusion detection system (IDS) has become a fundamental component of organizations that prevents cybercriminal …
The Controller Area Network (CAN) is the most widely used in-vehicle communication protocol, which still lacks the implementation of suitable security mechanisms such as …
H Qiu, T Dong, T Zhang, J Lu… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Deep learning (DL) has gained popularity in network intrusion detection, due to its strong capability of recognizing subtle differences between normal and malicious network activities …
Abstract Machine Learning (ML)-based Network Intrusion Detection Systems (NIDSs) have become a promising tool to protect networks against cyberattacks. A wide range of datasets …