This paper seeks to conduct a thorough systematic literature review (SLR) and offer a taxonomy of machine learning methods for malware detection that considers these problems by analyzing 77 chosen ...

Malware analysis and detection techniques include employing a malware honeypot, machine learning behavioral analysis, or using Nmap to help detect and mitigate it. The first stealth virus, ‘Brain’ ...

Artificial Intelligence (AI) provides a promising solution by automating and improving malware detection through the use of machine learning and deep learning models. This project explores the ...

The solution optimizes performance by pre-filtering files using machine learning and HyperDetect technology, sending only files requiring further analysis to the sandbox. After detonation, Bitdefender ...

Leveraging the power of Machine Learning as a tool, we delve into the realm of app permissions to discern the true nature of applications, whether they harbor malicious or benign intent. By analyzing ...

We use a variety of machine learning models that use different algorithms to predict whether a certain file is malware. Some of these algorithms are binary classifiers that give a strict ...

Using unsupervised machine learning techniques, security experts can cluster URLs or domains to identify DGAs (domain generation algorithms), used by malware creators to generate domains that act as ...

Josh’s research and presentation dove into the reasons why data science and machine learning apply to malware, and in particular malware detection, threat intelligence, malware analysis, as well ...

This paper seeks to conduct a thorough systematic literature review (SLR) and offer a taxonomy of machine learning methods for malware detection that considers these problems by analyzing 77 chosen ...