Constantinos Kolias, Ph.D.

Constantinos Kolias joined the Computer Science Department at the University of Idaho in 2018. Before that he served as a Research Assistant Professor under the supervision of Angelos Stavrou, in the CS Department at George Mason University. He received his doctorate in 2014 from the University of the Aegean under the supervision of Georgios Kambourakis. His main research interest revolves around security and privacy for the Internet of Things and critical infrastructures. He is also active in the design of intelligent Intrusion Detection Systems (IDS) with a special interest in privacy preserving distributed IDS. Other areas of interest include mobile and wireless communications security, and privacy enchasing techniques for the Internet. In 2015 he created and released the first wireless dataset specifically intended for research in wireless security, namely the AWID dataset. Today AWID has been downloaded and used as a benchmark by hundreds of organizations and universities.

Research

• RAIID: Resilient Attack Interceptor for Intelligent Devices, DOE-LDRD, PI:INL, 2019-2022 (Total Budget: $55OK, subcontracted $170K)

Focus Areas

• Security and privacy for the Internet of Things (IoT)
• Security for Industrial Systems, Smartgrid and Critical Infrastructures
• Distributed and Privacy-preserving Intrusion Detection Systems (IDS)
• Wireless communications security
• Development of testbeds for security purposes

• Kolias C, Borrelli RA, Barbara D, Stavrou A. Malware Detection in Critical Infrastructures Using the Electromagnetic Emissions of PLCs. Transactions of American Nuclear Society. 2019 Nov 1;121(1):519-22.
• Kolias, Constantinos, et al. "DDoS in the IoT: Mirai and other botnets." Computer 50.7 (2017): 80-84.
• Kambourakis, Georgios, Constantinos Kolias, and Angelos Stavrou. "The Mirai botnet and the IoT Zombie Armies." Military Communications Conference (MILCOM), MILCOM 2017-2017 IEEE. IEEE, 2017.
• Kolias, Constantinos, Vasilis Kolias, and Georgios Kambourakis. "TermID: a distributed swarm intelligence-based approach for wireless intrusion detection." International Journal of Information Security 16.4 (2017): 401-416.
• Kolias, Constantinos, et al. "Intrusion detection in 802.11 networks: empirical evaluation of threats and a public dataset." IEEE Communications Surveys & Tutorials 18.1 (2016): 184-208.