Coping with malware is getting more and more challenging, given their relentless growth in
complexity and volume. One of the most common approaches in literature is using machine …

The cyber world is plagued with ever-evolving malware that readily infiltrate all defense
mechanisms, operate viciously unbeknownst to the user, and surreptitiously exfiltrate …

Dynamic malware detection executes the software in a secured virtual environment and
monitors its run-time behavior. This technique widely uses API sequence analysis to identify …

Malware poses a severe threat to cyber security. Attackers use malware to achieve their
malicious purposes, such as unauthorized access, stealing confidential data, blackmailing …

Cyber attacks are currently blooming, as the attackers reap significant profits from them and
face a limited risk when compared to committing the “classical” crimes. One of the major …

Malware is one of the prevalent security threats. Sandboxes and, more generally,
instrumented environments play a crucial role in dynamically analyzing malware samples …

Automated dynamic malware analysis systems are important in combating the proliferation
of modern malware. Unfortunately, malware can often easily detect and evade these …

Many studies have proposed machine-learning (ML) models for malware detection and
classification, reporting an almost-perfect performance. However, they assemble ground …

The modern day cyber attacks are highly targeted and incorporate advanced tactics,
techniques and procedures for greater stealth, impact and success. These attacks are also …

Illicit crypto-mining leverages resources stolen from victims to mine cryptocurrencies on
behalf of criminals. While recent works have analyzed one side of this threat, ie: web …