Binary code similarityapproaches compare two or more pieces of binary code to identify their
similarities and differences. The ability to compare binary code enables many real-world …

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 …

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 …

While Deep Learning-based Network Intrusion Detection Systems (DL-NIDS) have recently
been significantly explored and shown superior performance, they are insufficient to actively …

The ever-growing volume of IoT traffic brings challenges to IoT anomaly detection systems.
Existing anomaly detection systems perform all traffic detection on the control plane, which …

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 …

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 …

Internet-of-Things IoT devices are increasingly targeted Uy adversaries due to their unique
characteristics such as constant online connection, lack of protection, and full integration in …

Malware classification is a difficult problem, to which machine learning methods have been
applied for decades. Yet progress has often been slow, in part due to a number of unique …

In this paper, we propose Segugio, a novel defense system that allows for efficiently tracking
the occurrence of new malware-control domain names in very large ISP networks. Segugio …