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RESULTS

  1. “SYNAPSE: An Integrated Cybersecurity Risk & Resilience Management Platform, With holistic Situational Awareness, Incident Response & Preparedness Capabilities” in ARES/IWAPS 2024 by Panagiotis Bountakas, Konstantinos Fyrasakis, et al.  
  2. “Uncovering Hidden Threats: Automated, Machine Learning-based Discovery & Extraction of Cyber Threat Intelligence from Online Sources” in IEEE CSR by Rafail A. Ellinitakis, Konstantinos Fysarakis, Panagiotis Bountakas, George Spanoudakis. 
  3. “Assessing the Complexity and Real-Time Performance of Anomaly Detection Algorithms in Resource-Constrained Environments” in IEEE ICCP by Romarick Yatagha, Oumayma Mejri, Karl Waedt, Christoph Ruland.  
  4. “Towards a Zero-Day Anomaly Detector in Cyber Physical Systems Using a Hybrid VAELSTM-OCSVM Model” in ACM CIKM by Romarick Yatagha, Betelhem Nebebe, Karl Waedt, Christoph Ruland.  
  5. “Modbus Covert Channels within Industrial Automation and Control Systems” in IEEE IECON by Erkin Kirdan, Karl Waedt. 
  6. “Safety and Cybersecurity under Emerging EU Legislation for Industry: A Use-case Driven Perspective” in ARES 2025, 20th International Conference on Availability, Reliability and Security by Ndèye Gagnessiry Ndiaye, Karl Waedt, Vangelis Photiou, Nikolaos Koulierakis and Vasiliki Danilatou.
  7. “FedMqADV: A unified framework for end-to-end evaluation of MQTT-based federated learning in adversarial setting” in 8th IEEE International Conference on Industrial CyberPhysical Systems (ICPS) by Ndeye Gagnessiry Ndiaye, Christoph Ruland, Karl Waed.  
  8. “Evading Detection: A Targeted Adversarial Attack on VAE-LSTM-Based Anomaly Detection in ICPS” in 2025 8th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) by Romarick Yatagha, Karl Waedt, Christoph Ruland.  
  9. “LLM-Powered Intent-Based Categorization of Phishing Emails” in CSR CRIRM – IEEE CSR Conference by Even Eilertsen, Vasileios Mavroeidis, Gudmund Grov.
  10. “Deep convolutional generative adversarial networks in image-based android malware detection” in Computers 13 (6), 154 by F Mercaldo, F Martinelli, A Santone. 
  11. “Evaluating the Impact of Generative Adversarial Network in Android Malware Detection” in ENASE, 590-597 by F. Martinelli, F. Mercaldo, A. Santone.  
  12. “A Federated Learning-Based Android Malware Detector Through Differential Privacy” in International Conference on Computer Aided Systems Theory, 307-319 by C. Peluso, G. Ciaramella, F. Mercaldo, A. Santone, F. Martinelli.  
  13. “Explainable Security Requirements Classification Through Transformer Models” in Future Internet 17 (1), 15 by L. Petrillo, F Martinelli, A Santone, F Mercaldo.  
  14. “Explainable ransomware detection with deep learning techniques” in Journal of Computer Virology and Hacking Techniques 20 (2), 317-330 by G. Ciaramella, G. Iadarola, F. Martinelli, F. Mercaldo, A. Santone.