Pro-ZD: A Transferable Graph Neural Network Approach for Proactive Zero-Day Threats Mitigation
#Zero-day threats #Graph Neural Networks #Firewall automation #Pro-ZD #Network security #Machine learning #arXiv
📌 Key Takeaways
- Researchers developed Pro-ZD, a Graph Neural Network model to address zero-day vulnerabilities in enterprise networks.
- The system targets risks created by automated firewall rule generation and dynamic access policies.
- Pro-ZD uses a transferable architecture, allowing it to function effectively even as network topologies change.
- The approach shifts cybersecurity from reactive fire-fighting to proactive simulations and risk mitigation.
📖 Full Retelling
🏷️ Themes
Cybersecurity, Artificial Intelligence, Network Infrastructure
📚 Related People & Topics
Machine learning
Study of algorithms that improve automatically through experience
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. Within a subdiscipline in machine learning, advances i...
Network security
Control of access to computer networks
Network security is an umbrella term to describe security controls, policies, processes and practices adopted to prevent, detect and monitor unauthorized access, misuse, modification, or denial of a computer network and network-accessible resources. Network security involves the authorization of acc...
Graph neural network
Class of artificial neural networks
Graph neural networks (GNN) are specialized artificial neural networks that are designed for tasks whose inputs are graphs. One prominent example is molecular drug design. Each input sample is a graph representation of a molecule, where atoms form the nodes and chemical bonds between atoms form the...
🔗 Entity Intersection Graph
Connections for Machine learning:
- 🌐 Large language model (7 shared articles)
- 🌐 Generative artificial intelligence (3 shared articles)
- 🌐 Electroencephalography (3 shared articles)
- 🌐 Computer vision (3 shared articles)
- 🌐 Natural language processing (2 shared articles)
- 🌐 Artificial intelligence (2 shared articles)
- 🌐 Neural network (2 shared articles)
- 🌐 Transformer (1 shared articles)
- 🌐 User interface (1 shared articles)
- 👤 Stuart Russell (1 shared articles)
- 🌐 Ethics of artificial intelligence (1 shared articles)
- 👤 Susan Schneider (1 shared articles)
📄 Original Source Content
arXiv:2602.07073v1 Announce Type: cross Abstract: In today's enterprise network landscape, the combination of perimeter and distributed firewall rules governs connectivity. To address challenges arising from increased traffic and diverse network architectures, organizations employ automated tools for firewall rule and access policy generation. Yet, effectively managing risks arising from dynamically generated policies, especially concerning critical asset exposure, remains a major challenge. Th