One of the main challenges in security today is defending against malware attacks. As
trends and anecdotal evidence show, preventing these attacks, regardless of their …

Machine Learning (ML) represents a pivotal technology for current and future information
systems, and many domains already leverage the capabilities of ML. However, deployment …

In this paper, we propose HyperVision, a realtime unsupervised machine learning (ML)
based malicious traffic detection system. Particularly, HyperVision is able to detect unknown …

Malware remains an important security threat, as miscreants continue to deliver a variety of
malicious programs to hosts around the world. At the heart of all the malware delivery …

An emerging Internet business is residential proxy (RESIP) as a service, in which a provider
utilizes the hosts within residential networks (in contrast to those running in a datacenter) to …

Both the operational and academic security communities have used dynamic analysis
sandboxes to execute malware samples for roughly a decade. Network information derived …

Machine Learning (ML) has become a valuable asset to solve many real-world tasks. For
Network Intrusion Detection (NID), however, scientific advances in ML are still seen with …

The detection and anti-detection of social botnets constitute an arms race that enables social
botnets to evolve quickly. Existing host-side detection approaches cannot easily detect every …

Internet-wide scanning depends on a notion of liveness: does a target IP address respond to
a probe packet? However, the interpretation of such responses, or lack of them, is nuanced …

Malware continues to be one of the major threats to Internet security. In the battle against
cybercriminals, accurately identifying the underlying malicious server infrastructure (eg, C&C …