144 citations · 250 across the 6 of their papers we have counts for
6 papers
Evaluating Adversarial Attacks on Federated Learning for Temperature Forecasting
Karina Chichifoi, Fabio Merizzi, Michele Colajanni
Deep learning and federated learning (FL) are becoming powerful partners for next-generation weather forecasting. Deep learning enables high-resolution spatiotemporal forecasts tha…
DOLOS: A Novel Architecture for Moving Target Defense
Giulio Pagnotta, Fabio De Gaspari, Dorjan Hitaj +3
Moving Target Defense and Cyber Deception emerged in recent years as two key proactive cyber defense approaches, contrasting with the static nature of the traditional reactive cybe…
Classification of Web Phishing Kits for early detection by platform providers
Andrea Venturi, Michele Colajanni, Marco Ramilli +1
Phishing kits are tools that dark side experts provide to the community of criminal phishers to facilitate the construction of malicious Web sites. As these kits evolve in sophisti…
Exploring the consequences of cyber attacks on Powertrain Cyber Physical Systems
Dario Stabili, Raffaele Romagnoli, Mirco Marchetti +2
This paper proposes a novel approach for the study of cyber-attacks against the powertrain of a generic vehicle. The proposed model is composed by a a generic Internal Combustion e…
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems
Giovanni Apruzzese, Mauro Andreolini, Luca Ferretti +2
The incremental diffusion of machine learning algorithms in supporting cybersecurity is creating novel defensive opportunities but also new types of risks. Multiple researches have…
Hardening Random Forest Cyber Detectors Against Adversarial Attacks
Giovanni Apruzzese, Mauro Andreolini, Michele Colajanni +1
Machine learning algorithms are effective in several applications, but they are not as much successful when applied to intrusion detection in cyber security. Due to the high sensit…