CV HAL - Franco Terranova

Publications

Multi-Taxonomy Vulnerability Classification with Hierarchically Finetuned Language Models

Franco Terranova , Sana Rekbi , Abdelkader Lahmadi , Isabelle Chrisment

DIMVA 2026 - Conference on Detection of Intrusions and Malware and Vulnerability Assessment, Jul 2026, Chania, Crete, Greece

Communication dans un congrès hal-05500820v2

When Performance Meets Security: Reducing Attack Paths in Virtual Machine Placement via Reinforcement Learning

Franco Terranova , Noura Limam , Abdelkader Lahmadi , Isabelle Chrisment , Raouf Boutaba

AISec 2026 - 19th ACM Workshop on Artificial Intelligence and Security, Nov 2026, The Hague, Netherlands

Communication dans un congrès hal-05749810v1

Scalable and Generalizable RL Agents for Attack Path Discovery via Continuous Invariant Spaces

Franco Terranova , Abdelkader Lahmadi , Isabelle Chrisment

2025 28th International Symposium on Research in Attacks, Intrusions and Defenses (RAID), Oct 2025, Gold Coast, Australia. pp.440-457, ⟨10.1109/RAID67961.2025.00029⟩

Communication dans un congrès hal-05182437v1

Leveraging Deep Reinforcement Learning for Cyber-Attack Paths Prediction: Formulation, Generalization, and Evaluation

Franco Terranova , Abdelkader Lahmadi , Isabelle Chrisment

The 27th International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2024), Sep 2024, Padua, Italy. pp.1-16, ⟨10.1145/3678890.3678902⟩

Communication dans un congrès hal-04662428v1

Deep Reinforcement Learning for Automated Cyber-Attack Path Prediction in Communication Networks

Franco Terranova , Abdelkader Lahmadi , Isabelle Chrisment

Geilo Winter School 2024 - Graphs and Applications, Jan 2024, Geilo, Norway

Poster de conférence hal-04462876v1

Projecting Latent RL Actions: Towards Generalizable and Scalable Graph Combinatorial Optimization

Franco Terranova , Guillermo Bernardez , Albert Cabellos-Aparicio , Nina Miolane , Abdelkader Lahmadi

2026

Pré-publication, Document de travail hal-05620445v1

Meta-Learning for Reinforcement Learning: Generalizing Agents to Unseen Scenarios

Franco Terranova , Omar Anser

Doctoral. The 25th European Agent Systems Summer School (EASSS 2025), POLITEHNICA University of Bucharest, Romania. 2025

Cours hal-05631945v1

De la sélection de paradigmes à la validation statistique: principes et bonnes pratiques en apprentissage automatique

Franco Terranova , Omar Anser

Doctoral. Atelier du Pôle AM2I : Mise en place de l’IA, Nancy, France. 2025

Cours hal-05636445v1

Deep Reinforcement Learning: Foundations and Practical Environment Setup for Real-World Applications

Franco Terranova

Doctoral. The 24th European Agent Systems Summer School (EASSS 2024), University College Dublin, Ireland. 2024

Cours hal-05631950v1

[BlackHat Arsenal 2026] Continuous CyberBattleSim: A More Realistic Simulation for AI-driven Attack Path Discovery

Franco Terranova , Abdelkader Lahmadi

2026

Vidéo hal-05670937v1

LaGCO-RL: Reinforcement Learning in Latent Action Spaces for Graph Combinatorial Optimization

Franco Terranova , Guillermo Bernardez , Albert Cabellos-Aparicio , Nina Miolane , Abdelkader Lahmadi

2026

Logiciel hal-05671095v1

Continuous CyberBattleSim

Franco Terranova , Abdelkader Lahmadi , Isabelle Chrisment

2025, ⟨swh:1:dir:0b32c22ea0771c26604e38728ab090df6469c4aa;origin=https://github.com/terranovafr/C-CyberBattleSim;visit=swh:1:snp:bc5aa14f7d947bec6111c51264e58ec506eeedac;anchor=swh:1:rev:7374c32b6711bb0e9b6d5fcd94d4eacc034c07cb⟩

Logiciel hal-05194047v1

Franco Terranova

Présentation

Domaines de recherche

Compétences

Publications

Publications

Multi-Taxonomy Vulnerability Classification with Hierarchically Finetuned Language Models

When Performance Meets Security: Reducing Attack Paths in Virtual Machine Placement via Reinforcement Learning

Scalable and Generalizable RL Agents for Attack Path Discovery via Continuous Invariant Spaces

Leveraging Deep Reinforcement Learning for Cyber-Attack Paths Prediction: Formulation, Generalization, and Evaluation

Deep Reinforcement Learning for Automated Cyber-Attack Path Prediction in Communication Networks

Projecting Latent RL Actions: Towards Generalizable and Scalable Graph Combinatorial Optimization

Meta-Learning for Reinforcement Learning: Generalizing Agents to Unseen Scenarios

De la sélection de paradigmes à la validation statistique: principes et bonnes pratiques en apprentissage automatique

Deep Reinforcement Learning: Foundations and Practical Environment Setup for Real-World Applications

[BlackHat Arsenal 2026] Continuous CyberBattleSim: A More Realistic Simulation for AI-driven Attack Path Discovery

LaGCO-RL: Reinforcement Learning in Latent Action Spaces for Graph Combinatorial Optimization

Continuous CyberBattleSim