Recent theoretical and practical studies have revealed that malware is one of the most
harmful threats to the digital world. Malware mitigation techniques have evolved over the …

This survey presents a comprehensive review of current literature on Explainable Artificial
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …

Malware detection approaches can be classified into two classes, including static analysis
and dynamic analysis. Conventional approaches of the two classes have their respective …

Malware is one of the most frequent cyberattacks, with its prevalence growing daily across
the network. Malware traffic is always asymmetrical compared to benign traffic, which is …

Due to digitization, a huge volume of data is being generated across several sectors such as
healthcare, production, sales, IoT devices, Web, organizations. Machine learning algorithms …

Owing to the prevalence of the Internet of things (IoT) devices connected to the Internet, the
number of IoT-based attacks has been growing yearly. The existing solutions may not …

The volume, type, and sophistication of malware is increasing. Deep convolutional neural
networks (CNNs) have lately proven their effectiveness in malware binary detection through …

Recently, there has been a huge rise in malware growth, which creates a significant security
threat to organizations and individuals. Despite the incessant efforts of cybersecurity …

Recent technological developments in computer systems transfer human life from real to
virtual environments. Covid-19 disease has accelerated this process. Cyber criminals' …

Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …