Antiviruses (AVs) are computing-intensive applications that rely on constant monitoring of
OS events and on applying pattern matching procedures on binaries to detect malware. In …

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 …

AntiViruses (AVs) are the main defense line against attacks for most users and much
research has been done about them, especially proposing new detection procedures that …

The use of Machine Learning (ML) techniques for malware detection has been a trend in the
last two decades. More recently, researchers started to investigate adversarial approaches …

Using a dataset containing about 50,000 samples from Brazilian cyberspace, we show that
relying solely on conventional machine-learning systems without taking into account the …

Persistent malware use techniques, such as obfuscation, process injection, and system call
abuse to evade security mechanisms and avoid detection throughout their compromise …

Malware analysis is an essential task to understand infection campaigns, the behavior of
malicious codes, and possible ways to mitigate threats. Malware analysis also allows better …

AntiViruses (AVs) are essential to face the myriad of malware threatening Internet users. AVs
operate in two modes: on-demand checks and real-time verification. Software-based real …

Malware and code-reuse attacks are the most significant threats to current systems
operation. Solutions developed to countermeasure them have their weaknesses exploited …

A promising avenue for improving the effectiveness of behavioral-based malware detectors
is to leverage two-phase detection mechanisms. Existing problem in two-phase detection is …