Short Bio

👋 Hi! I am Giuseppe Daidone, PhD student in Cybersecurity at Sapienza University of Rome and Luiss University, under the supervision of Prof. I. Masi and Prof. I. Amerini.

🔬 My research interests include adversarial machine learning techniques for designing secure AI models, multimedia forensics for detecting manipulated digital content, and deep learning based techniques for malware analysis.

Background

🖥 Work experience

• PhD Researcher, National Cybersecurity Agency (11/2025 - To date).

🎓 Academical background

• PhD in Cybersecurity, Sapienza University of Rome and Luiss University (current).
• Master’s degree in Engineering in Computer Science, Sapienza University of Rome (07/2025). Thesis: Adversarial Attacks on Convolutional and Transformer Architectures for Image-based Malware Detection and Classification Tasks, supervised by Prof. I. Amerini, co-supervised by Prof. L. Querzoni, co-examined by Prof. S. Bonomi.
• Bachelor’s degree in Computer Engineering, University of Bergamo (06/2023). Thesis: Exploration of Vulnerabilities Found in Electron Applications, supervised by Prof. S. Paraboschi and Seclab.

Long Formal Bio

Eng. Giuseppe Daidone is a PhD student in the Joint Cybersecurity Program at Sapienza University of Rome and Luiss University.

He has achieved a Bachelor’s Degree in Computer Engineering at the University of Bergamo in 2023, with the thesis Exploration of vulnerabilities found in Electron applications, under the supervision of Prof. S. Paraboschi and Seclab. He has achieved a Master’s Degree in Engineering in Computer Science at Sapienza University of Rome in 2025, specializing in Cybersecurity and Deep Learning fields intersection, with the thesis Adversarial Attacks on Convolutional and Transformer Architectures for Image-based Malware Detection and Classification Tasks, aligned with the objectives of the ArIS (Artificial Intelligence Sandboxing) PNRM Project of NAVARM (Naval Weaponry Direction of the Ministry of Defence) and Telsy, under the supervision of Prof. I. Amerini, co-supervision of Prof. L. Querzoni, and co-examining of Prof. S. Bonomi.

His research interests include (but not limited to):

• Adversarial machine learning techniques for designing secure Al models.
• Multimedia forensics for detecting manipulated digital content.
• Deep learning based techniques for malware analysis.

His research project focuses on Watermarking and Proactive Defense against Malicious Generative Al in collaboration with the National Cybersecurity Agency (ACN), President of the Council of Ministers. His PhD journey is supervised by Prof. I. Masi at OmnAl Lab, Department of Computer Science, Sapienza, and Prof. I. Amerini at ALCOR Lab, Department of Computer, Control and Management Engineering, Sapienza.

Since 2026, he has been a member of the Italian Intelligence Society (SOCINT) for intelligence studies.