In last decade, a proliferation growth in the development of computer malware has been
done. Nowadays, cybercriminals (attacker) use malware as a weapon to carry out the …

The increase in number and variety of malware samples amplifies the need for improvement
in automatic detection and classification of the malware variants. Machine learning is a …

Performing large-scale malware classification is increasingly becoming a critical step in
malware analytics as the number and variety of malware samples is rapidly growing …

Malware detection is one of the challenging tasks in network security. With the flourishment
of network techniques and mobile devices, the threat from malwares has been of an …

Malicious software deliberately affects the computer systems. Malware are analyzed using
static or dynamic analysis techniques. Using these techniques, unique patterns are …

As the malware research field became more established over the last two decades, new
research questions arose, such as how to make malware research reproducible, how to …

Currently, the detection of malware to prevent cybersecurity breaches is a raising a concern
for millions of people around the globe. Even with the most recent updates, antivirus …

With the widespread use of computers, the amount of malware has increased exponentially.
Since dynamic detection is costly in both time and resources, most existing malware …

As the malware threat landscape is constantly evolving and over one million new malware
strains are being generated every day [1], early automatic detection of threats constitutes a …

Dynamic malware analysis is fast gaining popularity over static analysis since it is not easily
defeated by evasion tactics such as obfuscation and polymorphism. During dynamic …