Speaker: Dr. Axel Sikora, University of Applied Sciences Offenburg, Germany
Title of Talk: AI Approaches for IoT Security Analysis
Biography: Axel Sikora holds a master (M.Sc. / Dipl.-Ing.) of Electrical Engineering and a master of Business Administration (MBA, Dipl. Wirt-Ing.), both from Aachen Technical University, Germany. He is a DAAD alumnus from 1990/91 in St Petersburg Politechnical Institute. He has done a Ph.D. (Dr.-Ing.) in Electrical Engineering at the Fraunhofer Institute of Microelectronics Circuits and Systems, Duisburg, with a thesis on SOI-technologies. After various positions in the telecommunications and semiconductor industry, he became a professor at the Baden-Wuerttemberg Cooperative State University Loerrach in 1999. In 2011, he joined Offenburg University of Applied Sciences, where he now leads the Institute of Reliable Embedded Systems and Communication Electronics (ivESK). Since Jan 2016, he is also deputy member of the board to Hahn-Schickard Association of Applied Research, one of the state-funded research institutes in Baden-Wuerttemberg, where he now leads two engineering divisions "Embedded Solutions" and "Software Solutions". Since October 2019, he is also affiliated professor to Technical Faculty of Freiburg University. His major interest is in the field of efficient, energy-aware, autonomous, secure and value-added algorithms and protocols for wired and wireless embedded communication with a strong focus on primary communication, gateway solutions, and data analytics for cyber-physical systems. Dr. Sikora is founder and shareholder of STACKFORCE GmbH, an independent and successul spin-off engineering company around IoT connectivity solutions. He is author, co-author, and editor and coeditor of several textbooks and more than 250 papers in the field of embedded design and wireless & wired networking. Amongst many other duties, he serves as Chairman of the annual embedded world Conference (Nuremberg), the world's largest event on the topic.
Abstract: IoT networks are increasingly used as entry points for cyber attacks, as often they offer low security levels, as they may allow the control of physical systems, and as they potentially also open the access to other IT networks and infrastructures. Existing Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) mostly concentrate on legacy IT networks. Nowadays, they come with a high degree of complexity and adaptivity, including the use of Artificial Intelligence (AI) and Machine Learning (ML). It is only recently, that these techniques are also applied to IoT networks. The keynote gives on overview of the state of the art of IoT network security and about AI-based approaches for the IoT security analysis.