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      • Research and development of advanced artificial

        intelligence solutions for the detection of cyber

        threats and defense against sophisticated attacks

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      • Project Objectives

        Main Objective of the Project

        The main objective of the project is to investigate methods, approaches, and tools for the effective detection of advanced cyberattacks employing specific adversarial tactics—namely exploitation, lateral movement, and privilege escalation—in accordance with the MITRE ATT&CK framework. Particular emphasis is placed on identifying the limitations of selected detection methods and proposing improvements to enhance their accuracy and efficiency in real-world operational environments.

        The project focuses on the systematic examination of techniques, sub-techniques, and procedures (TTPs) used within these attack tactics, the identification of their distinguishing characteristics, the analysis of existing detection approaches, and the formulation of recommendations aimed at improving the accuracy, efficiency, and adaptability of detection mechanisms across diverse operational environments.

      • Specific Project Objectives

        Analysis of Attack Techniques

        Analysis of techniques, sub-techniques, and procedures (TTPs) based on the MITRE ATT&CK framework, including the identification of limitations in existing detection mechanisms.

        Behavioral Analysis of Attacks and Identification of Detection Parameters

        Identification of indicators of compromise and behavioral patterns through the analysis of forensic and network data.

        Research on Models and Methodologies for Attack Detection

        Research and development of models leveraging artificial intelligence and machine learning for the detection of advanced cyberattacks.

        Identification of Limitations and Detection Optimization

        Optimization of detection models with a focus on accuracy, sensitivity, and computational efficiency under real-world conditions.

        Validation of Detection System Foundations

        Experimental validation of detection approaches in controlled and realistic testing environments.

        Capacity Building and Knowledge Transfer into Educational Curricula

        Integration of project outcomes into cybersecurity education and academic curricula.

      • Project Duration

        1

        4/2026

        Project Start

        2

        10/2029

        Project End

      • News

        FRI UNIZA Team at the EPI Cybersecurity 2026 Conference
        2026年10月5日
        As part of the project “Research and development of advanced artificial intelligence solutions...
        Can machine learning detect malware more accurately than humans? And where are its limits?
        2026年10月1日
        Can machine learning detect malware more accurately than humans? And where are its limits? These...
        Workshop: From Attack to Defense: A Series of Cybersecurity Workshops with Specialists from IstroSec
        2026年9月25日
        The Faculty of Management Science and Informatics, in cooperation with IstroSec, has prepared a...
      • Partners

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      Co-financed by the European Union through the Slovakia Programme under project No. NFP401101C360: Research and development of advanced artificial intelligence solutions for the detection of cyber threats and defense against sophisticated attacks.

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