In recent years, the scale of networks has substantially evolved due to the rapid
development of infrastructures in real networks. Under the circumstances, intrusion detection …

Due to factors such as differing distributions of training data and test data, false associations
between features and weight associations lead to unstable detection performance and lack …

The rapid rise of cyberattacks and the gradual failure of traditional defense systems and
approaches led to using Machine Learning (ML) techniques to build more efficient and …

The aim of the study is to detect and classify emotions from speech signals using Decision
Tree (DT) classifiers compared to Support Vector Machine (SVM) classifiers. Emotions are …

With the rapid advent of information technology and social networking, the multiplication of
connected devices further exposes users to the vulnerability of their personal data. This …

Abstract Connected and Autonomous Vehicles (CAVs) have expanded fast in recent years
and have started to affect people's daily lives. It is believed that CAVs could bring benefits …

The advancement of smart grids has addressed many challenges of traditional power grids,
yet it has also introduced new vulnerabilities to cyber-attacks that can disrupt power, leading …

In today's linked world, aircraft vehicles need advanced communication technologies to
operate. However, this dependency makes them susceptible to cyber dangers such …

Raw data gets transformed into features representing the problem in a more improved
manner. The problem gets represented in predictive models and in turn the accuracy is at a …

With the rapid increase in intrusion attempts exhibiting nonlinear behavior, network traffic
behaves unpredictably, and there is a massive feature in the problem domain, intrusion …