With the development of IoT devices, there is a rapid increase in new types of IoT malware
and variants, causing social problems. The malware's phylogenetic tree has been used in …

For efficiently handling thousands of malware specimens, we aim to quickly and
automatically categorize those into malware families. A solution for this could be the …

The number of IoT malware specimens has in-creased rapidly and diversified in recent
years. To efficiently analyze a large number of malware specimens, we aim to reduce the …

Recent years have witnessed lots of attacks targeted at the widespread Internet of Things
(IoT) devices and malicious activities conducted by compromised IoT devices. After some …

The recent emergence of consumer off-the-shelf embedded (IoT) devices and the rise of
large-scale IoT botnets has dramatically increased the volume and sophistication of Linux …

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 …

With the proliferation of malware on IoT devices, research on IoT malicious code has also
become more mature. Most studies use learning models to detect or classify malware …

Recently, malware targeting IoT devices has become more prevalent. In this paper, we
propose a practical AT tack detection and L ive malware A nalysis S ystem (ATLAS) that …

In this paper, we propose to cluster malware samples based on their TLSH similarity. We
apply this approach to clustering IoT malware samples as IoT botnets built from malware …

A drastic increase in cyberattacks targeting Internet of Things (IoT) devices using telnet
protocols has been observed. IoT malware continues to evolve, and the diversity of OS and …