Zero-day malware is malware that has never been seen before or is so new that no anti-
malware software can catch it. This novelty and the lack of existing mitigation strategies …

Fifth-generation (5G) mobile networks have already marked their presence globally,
revolutionizing entertainment, business, healthcare, and other domains. While this leap …

As smart grids (SGs) increasingly rely on advanced technologies like sensors and
communication systems for efficient energy generation, distribution, and consumption, they …

This article explores deep learning models in the field of malware detection in cyberspace,
aiming to provide insights into their relevance and contributions. The primary objective of the …

Conventional malware detection approaches have the overhead of feature extraction, the
requirement of domain experts, and are time-consuming and resource-intensive. Learning …

The Android operating system has long been vulnerable to malicious software. Existing
malware detection methods often fail to identify ever-evolving malware and are slow in …

Malware has evolved to pose a major threat to information security. Efficient anti-malware
software is essential in safeguarding confidential information from these threats. However …

The increasing prevalence of unknown-type attacks on the Internet highlights the importance
of developing efficient intrusion detection systems. While machine learning-based …

With the fast development of the Internet of Things (IoT), the growing amounts of data
transmitted through edge devices tempt hackers to attack vulnerabilities. Because of data …

In the realm of smart grids, machine learning (ML) detectors—both binary (or supervised)
and anomaly (or unsupervised)—have proven effective in detecting electricity theft (ET) …