Owing to the exponential proliferation of internet services and the sophistication of
intrusions, traditional intrusion detection algorithms are unable to handle complex invasions …

In recent days, cyber-physical systems (CPS) have become a new wave generation of
human life, exploiting various smart and intelligent uses of automotive systems. In these …

Recently, many studies have focused on payload analysis. However, these studies mostly
apply image-based deep classifiers for layer 7 traffic analysis and not specifically for …

In this paper, an optimized classification approach based on a support vector machine
(SVM) classifier is proposed to maximize the accuracy of a machine learning model …

For the following problems: information loss in the original pool layer of CNN and the
gradient disappearance in the processing of long sequence data by RNN, an intrusion …

As Internet of Things (IoT) is rapidly developing and popularizing, IoT devices generate a
large amount of network traffic information, which requires reliable IoT traffic intrusion …

Network intrusion detection is a constantly evolving field with researchers and practitioners
constantly working to keep up with novel attacks and growing amounts of network data …

Fog computing efficiently brings services to the edge network because it facilitates
processing, communication, and storage to be closer to the edge devices. Fog computing is …

Contemporary attackers, mainly motivated by financial gain, consistently devise
sophisticated penetration techniques to access important information or data. The growing …

To address the problem of network security situation assessment in the Industrial Internet,
this paper adopts the evidential reasoning (ER) algorithm and belief rule base (BRB) …