In this survey, we review the key developments in the field of malware detection using AI and
analyze core challenges. We systematically survey state-of-the-art methods across five …

The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …

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

Malware attacks continue to evolve, making detection challenging for traditional static and
dynamic analysis techniques. On the other hand, memory analysis provides valuable …

The aim of this systematic literature review (SLR) is to provide a comprehensive overview of
the current state of Windows malware detection techniques, research issues, and future …

The detection of malware is a complex problem in the area of Internet security. Develo** a
malware defense system that is less costly to detect large-scale malware is needed. This …

This paper presents a wavelet-based real-time automated fire detection algorithm that takes
into consideration the multi-resolution property of the wavelet transforms. Unlike …

With the significant growth in Industrial Internet of Things (IIoT) technologies, various IIoT-
based applications have emerged in the last decade. In recent years, various malware …

Android is the most widely used mobile platform, making it a prime target for malicious
attacks. Therefore, it is imperative to effectively circumvent these attacks. Recently, machine …

In previous years, cybercriminals have utilized various strategies to evade identification,
including obfuscation, confusion, and polymorphism technology, resulting in an exponential …