EuroCybersec2021 Workshop

By October 28, 2021News

The IoTAC project thanks everyone, all speakers and attendees, to make the one-and-a-half-day EuroCybersec2021 workshop a real success.

The over 40 participants learned about state of art European cyber security research from our H2020 project partners CityScape and Fishy as well as from other presenters from Germany, Greece, Hungary, Italy, Poland, Portugal, Spain and also from Australia.

We discussed various subjects of cyber security and related technologies, including authentication and authorisation, attack detection, the use of artificial intelligence, machine learning and deep learning as well as human-centric design and automated software vulnerability prediction. Other security-related aspects like device attestation and IoT certification were also covered. Further presentations introduced the application of these technologies in diverse environments like multimodal transportation, connected cars and drone operation.

Encouraged by the success of the event we plan to continue it also next year and may also organize further workshops with more focused content targeting specific aspects of cyber security.

Program of the workshop:

25 October 2021   

Overviews and IoT Security Technologies
Session Chair: Erol Gelenbe (IITIS)

The IoTAC Project: Technology and Research Perspectives by Dionysios Kehagias, ITI-CERTH, Thessaloniki, Greece

The European project CitySCAPE on Cybersecurity for Multi-Modal Transport Systems  by F. Giampaolo, Engineering Ingegneria Informatica S.p.A., A. D’Arcangelo, Kaspersky, L. Bianconi, Gruppo SIGLA  S.R.L., Italy.

Front-end Access Control: The centre piece of Zero Trust security IoT Security Trust Mark™ Certification & Voluntary Labelling Scheme by Matt Tett, Advisor – Subject Matter Expert, IoT Security Trust Mark™ Scheme

Research for the Security of the IoT (I)
Session Chair:  Marija Jankovic (ITI)

Application of a Human-Centric Approach in Security by Design for IoT Architecture Development by Violeta Vasileva, Artshare Ltd

Mitigating the Massive Access Problem in the IoT by E. Gelenbe, Mert Nakip, Dariusz Marek, Tadeusz Czachorski (IITIS)

Secure Authentication for everyone! Enabling 2nd-factor Authentication under Real-world constraints by Julian Fietkau, Syeda Mehak Zahra, and Markus Hartung, Technical University of Berlin

T-RAID: TEE-based Remote Attestation for IoT Devices by  Roland Nagy, Márton Bak, Dorottya Papp, Levente Buttyán, Laboratory of Cryptography and System Security (CrySyS Lab), Budapest University of Technology and Economics

Auto-Associative Random Neural Network Detection of Botnets by Mert Nakip and Erol Gelenbe (IITIS)

An Empirical Evaluation of the Usefulness of Word Embedding Techniques in Deep Learning-based Vulnerability Prediction by Ilias Kalouptsoglou1,2 , Miltiadis Siavvas1 , Dionysios Kehagias1 , Alexandros Chatzigeorgiou2 , and Apostolos Ampatzoglou21 Centre for Research and Technology Hellas, Thessaloniki, Greece, University of Macedonia, Thessaloniki, Greece

26 October 2021

Research for the Security of the IoT (II)
Session Chair:  Tadeusz Czachorski (IITIS)

Correlation-based Anomaly Detection for the CAN Bus by András Gazdag1, György Lupták1, and Levente Buttyán2Laboratory of Cryptography and System Security (CrySyS Lab), Budapest University of Technology and Economics , and Ukatemi Technologies

Energy and QoS Aware Security Services at the Edge by E. Gelenbe, Piotr Frohlich and Mateusz Nowak

Research for the Security of the IoT (III)
Session Chair:  Andras Vilmos (Safepay)

The Adversarial Random Neural Network and its use for Attack Detection in a Large Network by E. Gelenbe and M. Nakip (IITIS)

A Machine Learning Intrusion Detection System for Known and Unknown Anomalies by E. Simo, F. Aguilo, E. Marin, X. Massip, A. Hussain and M. Mahmoudi, CRAAX, UPC (Barcelona), Spain

System Vulnerability Prediction using the Adversarial Random Neural Network by E. Gelenbe, M. Nakip, IITIS, PL and Ilias KalouptsoglouMiltiadis Siavvas, Dionysios Kehagias, ITI-CERTH, GR

Leave a Reply

eighteen + four =