SESSION 3 - Cybersecurity, artificial intelligence, data mining, big data analysis, and DSS applied to CBRNe


Prof. Oleg Illiashenko

National Aerospace  University -  "KhAI" - Kharkiv



Institute of information science and technologies "A. Faedo" (ISTI-CNR)



Prof. Parag Chatterjee

National Technological University (Universidad Tecnológica Nacional), Buenos Aires



Dept. of Biological Engineering, University of the Republic (Universidad de la República)



Dr. Riccardo Rossi

Department of  Industrial Engineering  - University of Rome Tor Vergata


This session will host presentations based on the following description.


Cybersecurity is becoming crucial, as more information and advanced technology are being made available in cyberspace. As recent events have demonstrated, cyberspace must be considered the new theatre of warfare and has the potential to undermine the stability of a country. New terms, such as cyberwarfare and cyberterrorism, were coined to better describe this threat and there is growing concern among governments, that they are not ready to fully face such an emerging menace. More critical infrastructures today are remotely controlled via software systems that, while increasing efficiency, determine new vulnerabilities. Otherwise, innovative technologies such as Artificial Intelligence, Machine Learning, and Big Data Analysis allow for improving risk mitigation in systems’ cybersecurity. In this scenario, CBRNe Intelligence plays an extremely important role in preventing the malicious use of, an otherwise beneficial, asset. A Decision Support System (DSS) can be seen as both a tool to help the decision-making process in the aftermath of a CBRNe event, as well as a tool to optimize the planning and management of operations. Today, DSSs are essential instruments in coping with problems that may not have been identified in advance and are changing rapidly, or when dealing with large amounts of data. DSSs are interactive software-based systems intended to help decision-makers to gather useful information from a combination of raw data, documents, and personal knowledge. Therefore, DSSs greatly assist in the identification and solving of problems, hence the decision-making process. In this regard, DSSs can be extremely helpful when applied to CBRNe Prediction, Planning, and Emergency Management. 

This session will host the work of the experts that will reflect those concepts.

Keywords: Cyberthreats problems and protection; Critical infrastructure risks and control; Internet of Things and Artificial Intelligence to prevent emergencies and reduce risks during disasters;  Big data analysis and data mining; Big Data Analytics and Data Mining Applied to Safety & Security; Software and ICT Tools for Safety & Security; CBRNe Events — Prediction and Management; Predictive Analytics in Risk Management; Cybersecurity and modern cyber-warfare & cyber-terrorism; Artificial Intelligence Towards Safety & Security; ICT Vulnerabilities and Computational Aspects of Safety & Security; Privacy Issues in IoT, AI and Smart Systems; Intelligent Systems in Risk Management; Decision Support Systems in Safety & Security; Big Data Analysis; Data Mining Applied to Safety & Security; Deep Learning; Machine Learning; Software and Tools for Safety & Security; CBRNe Events Prediction and Management

Here it is the list of the oral presentations of technical session 3.

The abstract will be available on the book of abstract.

You can complete the registration to participate at our conference here: LINK

You can consult the program and the scheduling of the presentation here: LINK

49.TS3. Dependable robotic-biological systems for detection and identification of explosive ordnances: IDEM project.

Vyacheslav Kharchenko(1), Herman Fesenko(1), Gennadiy Fedorenko(1), Volodymyr Pavlikov(2), Igor Kliushnikov(1), Oleg Illiashenko(1,3), Igor Tolkunov(4)

1. Computer Systems, Networks and Cybersecurity Department, National Aerospace University KhAI, Kharkiv, Ukraine

2. National Aerospace University KhAI, Kharkiv, Ukraine

3. Institute of Information Science and Technologies “Alessandro Faedo”, Area della Ricerca CNR di Pisa, Pisa, Italy

4. Pyrotechnics and Special Training Department, National University of Civil Defence of Ukraine, Kharkiv, Ukraine


50.TS3. The influence of the environment on the diffusion of COVID-19 using advanced statistics and causality detection techniques.

Andrea Murari(1,2), Riccardo Rossi(3) and Michela Gelfusa(3)

1. Consorzio RFX (CNR, ENEA, INFN, Università di Padova, Acciaierie Venete SpA), Padova, Italy 

2. Istituto per la Scienza e la Tecnologia dei Plasmi, CNR, Padova, Italy 

3. Department of Industrial Engineering, University of Rome “Tor Vergata”, Rome, Italy


51.TS3. Importance of Artificial Intelligence and Robotics lap for Implementation Excellence in Fire Station on Industrial Area in Abu Dhabi.

Abdulla Alhmoudi(1)

1. Abu Dhabi Civil Defence Authority, United Arab Emirates.


52.TS3. Machine and Deep Learning Tools applied to CBRNe Events: An Overview of QEP Research Group Activities.

Riccardo Rossi(1), Luca Martellucci(1), Alessandro Puleio(1), Novella Rutigliano(1), Ivan Wyss(1), and Pasquale Gaudio(1)

1. Department of Industrial Engineering, University of Rome “Tor Vergata”,  Italy


53.TS3. Improving cyber security awareness: a crucial measure to prevent cyber attacks.

Marco Campanini(1), Claudio Paganelli(1)

1. Avv. Marco Campanini, Rome, Italy


54.TS3. Evidence-based cybersecurity assessment of programmable systems to ensure the protection of CBRNe IT infrastructure.

Oleg Illiashenko(1,2), Vyacheslav Kharchenko(1), Eugene Babeshko(2), Oleksandr Letychevskyi(3), Oleg Odarushchenko(4)

1. Department of computer systems and networks, National Aerospace University “KhAI”, Kharkiv, Ukraine 

2. Software Engineering & Dependable Computing Laboratory, Institute of Information Science and Technologies “A.Faedo”—ISTI CNR, Pisa, Italy 

3. Digital automata theory department, V.M. Glushkov Institute of Cybernetics of NAS of Ukraine, Kyiv, Ukraine 

4. Research and Production Enterprise RPC Radics LLC, Kropyvnytskyi, Ukraine


55.TS3. Hierarchical BBN-based approach for SMR digital infrastructure dependencies assessment under MUPSA framework.

Eugene Brezhniev(1), Vyacheslav Kharchenko(1), Oleksandr Gordieiev(2)

1. National Aerospace University (KhAI), Department of Computer Systems, Networks and Cybersecurity, Kharkiv, Ukraine

2. Lutsk National Technical University, Software Engineering Department, Lutsk, Ukraine


56.TS3. Robots as a Mobile Sensors Platform: Decision Support and Decision Augmentation for CBRNe Emergency.

Carmine Grelle(1), Alessandro Zacchei(2), Claudio Chieppa(3), Anna Kostihova(4,5), Roberto Fiorito(4,6)

1. Chief Executive Officer SHIELD REPLY, Rome, Italy

2. Chief Technology Officer EUROLINKS SYSTEM, Rome, Italy 

3. Senior Consultant CONCEPT REPLY, Turin, Italy 

4. Tor Vergata University of Rome, Faculty of Medicine and Surgery – Master International Security/Safety, Global Strategies and Medical Maxi-Emergency in the Non-Conventional Events: Analyses and Management, Rome, Italy 

5. ASST Santi Paolo e Carlo, Milano, Emergency Department, Milan, Italy 

6. Tor Vergata University of Rome, Faculty of Medicine and Surgery – Department of Biomedicine and Prevention, Rome, Italy


57.TS3. The AI Act: its impact on Cybersecurity and privacy domains between the definition of "artificial intelligence system" and the risk-based approach.

Nicola Fabiano(1,2,3)

1. Studio Legale Fabiano - Rome, Italy

2. University of Ostrava - Rome, Italy

3. International Institute of Informatics and Systemics - USA, United States of America


58.TS3. Artificial Intelligence and Predictive Healthcare in CBRNE incidents.

Parag Chatterjee(1)

1. University of the Republic, Uruguay


59.TS3. Digital Twins-based Intelligent Systems of Monitoring Critical Objects: Methodology and Models of Availability Assessment.

Vyacheslav Kharchenko(1), Olga Morozova(1), Vladislav Shcheglov(1), Vitalii Gaievskyi(2)

1. Department of Computer Systems, Networks and Cybersecurity of National Aerospace University "KhAI", Kharkiv, Ukraine



60.TS3. CISReF: Regional Health and Pharmacovigilance Information Dashboard.

Daniele Distefano(1), Rossana Moroni(2), Antonio Parrilla(3), Michele Tricarico(4)

1. Ministero dell’Istruzione – Ufficio Scolastico Territoriale di Milano, Milan, Italy 

2. Ministero della Salute - Direzione generale della digitalizzazione, del sistema informativo sanitario e della Statistica, Rome, Italy 

3. Presidenza del Consiglio dei Ministri – Dipartimento per lo Sport, Servizio III – Comunicazione, eventi sportivi, studi e ricerche, Rome, Italy 

4. AIFA – Settore ICT, Rome, Italy