22/02/2022 18:02:05

Accepted Special Sessions


Organisers of Special Sessions are responsible for:

  • Select a topic of interest to conference delegates.
  • Obtain papers on this topic, normally at least 5 for an invited special session, but often more. At least 60% of the papers must be by authors that are neither session chairs from their team nor reviewers for the session. 
  • If there are not sufficient papers, final accepted papers will be moved to the general track.
  • Manage the review process for these papers on due time and deadlines.
  • Provide suitable reviewers for the reviews of the papers.
  • Ensure the final versions of the papers are uploaded before the deadline.
  • Attend the conference, and chair the session.
  • Provide a list of international reviewers (name, affiliation, country) who have already accepted to review the papers.
  • Disseminate a call for papers for the special session widely.



Special Session 1

Computational Intelligence for Industrial Cybersecurity (CIIS)

  • Mike Winterburn – Technological University of the Shannon, Ireland
  • Michael Hellwig – Vorarlberg University of Applied Sciences, Austria
  • Álvaro Herrero – University of Burgos, Spain
  • Stephen McCombie – NHL Stenden University of Applied Sciences, Netherlands
  • Nuno Lopes – Polytechnic of Cávado and Ave, Portugal

Industry 4.0 is driving the convergence of Information technology (IT) and Operational Technology (OT) and is resulting in the broader deployment of Industrial Internet of Things (IIoT) technologies. This gives rise to complex heterogeneous distributed systems, particularly in manufacturing and maritime environments. Such systems can consist of 1) OT, such as programmable logic controllers, computer numerical control systems, and complex industrial control systems, including the supervisory control and data acquisition systems, and 2) IT, such as databases, data integration tools, data visualization systems, reporting systems, AI systems and additionally 3) IIoT such as distributed sensors, smart robotics, track and trace systems and even augmented reality. Industry 4.0 cybersecurity management has consequently become a difficult challenge. Systems communicate using various standards and protocols, sometimes distributed over large geographic areas. In addition, they use a diverse mix of hardware and software components and consist of different physical infrastructures. This means that traditional cybersecurity management tools such as firewalls, Intrusion Detection and Intrusion Prevention Systems (IDS/IPS), application log monitors, and network monitoring tools are becoming increasingly limited. To fill this gap, this special session aims to present innovative applications of Computational Intelligence in the industrial domain.


Special Session 2

Disinformation Detection (DisDet)

  • Michał Choraś – Bydgoszcz University of Science and Technology, Poland.
  • Rafał Kozik – Bydgoszcz University of Science and Technology, Poland.
  • Paweł Ksieniewicz – Wroclaw University of Science and Technology, Poland.
  • Michał Woźniak – Wroclaw University of Science and Technology, Poland.

The problem of spreading fake news (disinformation) is not new and has already been reported in ancient times. Still, it has started having a huge impact, especially on social media users. Therefore, such false information should be detected as soon as possible to avoid its negative influence on the readers and, in some cases, on their decisions, e.g., during the election. Therefore, the methods which can effectively detect fake news are the focus of intense research. The main aim of this section is to bring together researchers and scientists from basic computing disciplines (computer science and mathematics), experts in legal and societal aspects as well as researchers from various application areas who are pioneering fake news analysis methods to discuss problems and solutions in this area, to identify new issues, and to shape future directions for research. Session topics include, but are not limited to:

  1. fake news detection in social media
  2. fake news detection in images and video
  3. NLP methods for disinformation detection
  4. architectural frameworks and design for fake news detection
  5. learning how to detect the fake news in the presence of concept drift
  6. learning how to detect the fake news with limited ground truth access and based on limited data sets, including one-shot learning
  7. feature selection and extraction methods for fake news detection
  8. proposing how to compare and benchmark the fake news detectors
  9. case studies and real-world applications
  10. legal, ethical and societal aspects of fake news detection
  11. data protection and GDPR in fake news detection
  12. explainability for fake news detection


Special Session 3

New methods and models to study the Spread of Malware and Fake News (SMFN)

  • Angel Martin del Rey – Universidad de Salamanca, Spain.
  • Roberto Casado Vara – Universidad de Burgos, Spain.
  • Angel Tocino Garcia – Universidad de Salamanca, Spain.

This special session is devoted to gathering high-quality research papers and reviews focused on the design (qualitative, numerical, and statistical) analysis and computational implementation of mathematical models to simulate the propagation of malicious code (malware) and fake news or misinformation. Specifically, this special session will cover different perspectives on these and related potential topics:

  1. Design and analysis of novel epidemiological models (for malware and fake news) based on deterministic and stochastic differential equations.
  2. Analysis of new techniques based on Artificial Intelligence and Complex Network Analysis for designing and studying individual-based epidemiological models.
  3. Analysis of the relation and analogies of the propagation of different entities: biological agents, malicious code, fake news, etc.
  4. Detection and early detection of malware and fake news spreading based on data mining, deep learning, XAI, etc.
  5. Study of novel methodologies to control malware and misinformation epidemics.