Specification of the department's research focus

Research directions:

 Intelligent methods in analytics and cybersecurity

Currently, the field of information technology faces multiple challanges. These include the pressure for ubiquitous and interconnected IT infrastructure, leading to increased complexity and the need to improve the planning, analysis, and design of information systems, including related IT assets. Additionally, there is a demand for methods and techniques that mimic human analytical, creative, and decision-making capabilities. Finally, there is a requirement for high availability of IT services and associated cyber resilience in the face of growing threats and increasingly sophisticated attacks. The common denominator of these challenges is the rising demand for analytical and adaptive approaches, methods, and techniques that ensure the effective utilization of data and information resources.

A key research domain is artificial intelligence and the development of algorithmic solutions for tasks requiring adaptation, learning, and other manifestations of human intelligence. The vast space of research problems, ranging from classification and segmentation to the detection of complex image structures and natural language processing, is offered by the field of machine learning. For the exploration of nonlinear emergent phenomena and the optimization of complex systems, agent-based approaches can be applied. The ability for autonomous decision-making and interaction between agents can be utilized to simulate various societal or economic tasks. Here, approaches from systems thinking and system dynamics can also be employed to explore causal loops and identify feedback mechanisms. A crucial prerequisite for the automated processing of knowledge-intensive tasks is a suitable form of knowledge representation. Conceptual and ontological modeling introduces new ways to capture knowledge and interconnect it using entities, relationships, and defined constraints. This offers vast potential for application in areas rich in expertise, such as healthcare, construction, aviation, or education. There is also a close relationship with decision-making models and research on systems under conditions of complexity and uncertainty using the principles of fuzzy logic.

Cybersecurity and information security are also among the essential research areas in today’s IT world. Research in this direction focuses on developing innovative methods to secure industrial systems, Internet of Things (IoT) devices, and critical infrastructure, including energy and healthcare systems. It covers the design of advanced security architectures, dynamic modeling of cyber threats and their simulation, as well as the application of expert systems with AI elements for attack prevention and detection. Special attention is given to securing IoT devices, which often constitute a key part of modern infrastructure, and to collaboration with partners from both industry and the public sector.

 

Subtopics:

• Artificial Intelligence
• Machine Learning: Designing and applying advanced algorithms and techniques for descriptive, predictive, optimization, and generative tasks.
• Intelligent Agents: Modeling and simulation of complex social, economic, and other systems.
• Knowledge Representation: Specification of concepts and relationships within a selected domain.
• Natural Language Processing and Large Language Models: Developing and applying techniques and models for text understanding and generation.
• Decision Support
• Fuzzy Decision Models: Models enabling adaptive system control under conditions of complexity and uncertainty.
• Game Theory: Decision-making scenarios and optimization strategies for actors based on defined objectives and constraints.
• Modeling
• Process Modeling: Optimization of business process models to help identify and eliminate inefficiencies.
• System Dynamics Modeling: Analysis and representation of causal dependencies, including system behavior prediction over time.
• IT Infrastructure and Cybersecurity
• IoT Device Security: Designing encryption protocols and anomaly detection systems to protect smart homes, cities, and industrial applications.
• Energy System Protection: Collaboration with Hitachi to secure smart grids and distribution networks.
• Real-Time Anomaly Detection Using AI: Applying machine learning for the prevention and detection of cyberattacks on critical infrastructure.
• Cyber Threat Modeling and Crisis Management: Simulating and developing measures to enhance resilience to attacks.
• Security Architectures and Policies: Designing strategies for the cyber protection of industrial and energy systems.
• Smart Technologies: Architectures of network components and other IoT devices, optimization of sensor networks, and connection sharing.

 

Projects:

Project Name: Utilization of Artificial Intelligence for Ensuring Cybersecurity in Smart Cities

Project Number: VJ02010016

Duration: 2022–2025

Primary Provider: Ministry of the Interior of the Czech Republic

Program: Strategic Support for the Development of Security Research in the Czech Republic 2019–2025 (IMPAKT 1)

Responsible Investigator: Assoc. Prof. Vladimír Soběslav, Ph.D.

Partners: Brno University of Technology

 

Project Name: Application of Dynamic System Models for Ensuring Cybersecurity of Energy Substation Systems

Project Number: TS01020105

Duration: 2024–2027

Primary Provider: Technology Agency of the Czech Republic

Program: Théta

Responsible Investigator: Assoc. Prof. Josef Horálek, Ph.D.

Partners: Hitachi Energy

 

Project Name: Integration of AI and Technological Upgrade of the DMS Application eDoCat

Project Number: CZ.01.01.01/08/23_036/0005277

Duration: 2024–2026

Primary Provider: Ministry of Industry and Trade

Program: Proof of Concept 2

Responsible Investigator: Assoc. Prof. Pavel Čech, Ph.D.

Partners: Onlio, a.s.

 

International Collaboration:

• Florida Institute for Human and Machine Cognition (IHMC), USA
• Institute of Human Centred Engineering, University of Technology Malaysia, Malaysia