This proposed model introduces novel deep learning methodologies. The objective here is
to create a reliable intrusion detection mechanism to help identify malicious attacks. Deep …

Network intrusion detection systems play a critical role in protecting a variety of services
ranging from economic through social to commerce. However, the growing level and …

The widespread adoption of the Internet of Things (IoT) across various domains has ushered
numerous applications into our daily lives. Ensuring the security of sensitive data, including …

Purpose: As the complexity and diversity of cyberattacks continue to grow, traditional
security measures fall short in effectively countering these threats within web-based …

In the current digital age, the volume of data generated by various cyber activities has
become enormous and is constantly increasing. The data may contain valuable insights that …

Internet of Things (IoT) applications are experiencing a significant surge in popularity.
However, this rapid growth is accompanied by various challenges, for example, the gigantic …

A distributed denial-of-service (DDoS) attack is a cyber-attack that aims to disrupt the regular
traffic of a targeted server, service, or network by inundating the target or its surrounding …

Deep learning (DL) has revolutionized machine learning tasks in various domains, but
conventional DL methods often demand substantial amounts of labeled data. Semi …

Currently, the internet serves as the predominant means of communication and is utilized by
a vast number of individuals worldwide. Simultaneously, the commercial aspect of the …

Several security issues, such as the forgery of information-sharing channels, hardware
components, and operating systems, hampered the steady expansion of cyber-physical …