Malware-based abuses of IoT devices are the focus here. We will learn about analysis and classification of 150,000 samples of IoT related malware. Scaling of code level analysis of IoT malware samples can help us to better detection and better understanding of the situation. Presentation will also give some insight about building sandbox environments and explaining how to avoid malware to circumvent analysis in the environment.

Dr. Boldizsár Bencsáth has M.Sc. and Ph.D. degrees in Computer Science from the Budapest University of Technology and Economics (BME), as well as M.Sc. degree in economics from the Budapest University of Economics. From 1999, he is member of the Laboratory of Cryptography and Systems Security (CrySyS) of BME. His research interests are in network security, including DoS attacks, spam, malware, botnets, and cyber-physical system security.