The struggle between security analysts and malware developers is a never-ending battle
with the complexity of malware changing as quickly as innovation grows. Current state-of-the …

In the Internet age, malware (such as viruses, trojans, ransomware, and bots) has posed
serious and evolving security threats to Internet users. To protect legitimate users from these …

In this paper we introduce a deep neural network based malware detection system that
Invincea has developed, which achieves a usable detection rate at an extremely low false …

Co** 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 …

Both researchers and malware authors have demonstrated that malware scanners are
unfortunately limited and are easily evaded by simple obfuscation techniques. This paper …

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 …

The results of botnet detection methods are usually presented without any comparison.
Although it is generally accepted that more comparisons with third-party methods may help …

Labeling a malicious executable as a variant of a known family is important for security
applications such as triage, lineage, and for building reference datasets in turn used for …

Dynamic taint analysis and forward symbolic execution are quickly becoming staple
techniques in security analyses. Example applications of dynamic taint analysis and forward …

Anti-virus vendors are confronted with a multitude of potentially malicious samples today.
Receiving thousands of new samples every day is not uncommon. The signatures that …