Abstract Machine Learning (ML) and Deep Learning (DL) have achieved high success in
many textual, auditory, medical imaging, and visual recognition patterns. Concerning the …

Concerns about cybersecurity and attack methods have risen in the information age. Many
techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs) …

Machine learning models have made many decision support systems to be faster, more
accurate, and more efficient. However, applications of machine learning in network security …

Due to their massive success in various domains, deep learning techniques are increasingly
used to design network intrusion detection solutions that detect and mitigate unknown and …

Due to the emerging network security vulnerabilities and threats, securing the network and
identifying malicious network traffic is crucial for various organizations. One critical aspect of …

An intrusion detection system (IDS) is an effective tool for securing networks and a
dependable technique for improving a user's internet security. It informs the administration …

As an important technology in the field of cyberspace security, image steganography is of
great strategic significance to the research of image steganography. With the wider …

Abstract Recently, Software Defined Networking (SDN) has emerged as the key technology
in programming and orchestrating security policy in the security operations centers (SOCs) …

Intrusion detection systems (IDS) are a very vital part of network security, as they can be
used to protect the network from illegal intrusions and communications. To detect malicious …

The new paradigm of nature-inspired cybersecurity can establish a robust defense by
utilizing well-established nature-inspired computing algorithms to analyze networks and act …