GRAPHSEC – Advancing the Application of AI/ML to Network Security through Graph Neural Networks

The application of Artificial Intelligence (AI) and Machine Learning (ML) to network security (AI4SEC) is paramount against cybercrime. While AI/ML is today mainstream in domains such as computer vision and speech recognition, it has produced below-par results in AI4SEC. Solutions do not properly generalize, are ineffective in real deployments, and are vulnerable to adversarial attacks. A fundamental limitation is the lack of AI/ML technology specific to network security. Network security data is intrinsically relational, and graph-structured data representations and Graph Neural Networks (GNNs) have the potential to drastically advance the AI4SEC domain. In this positioning paper we propose GRAPHSEC, a research agenda to systematically integrate GNNs in AI4SEC. We structure the state of the art in AI4SEC and on the application of GNNs to network security applications, elaborate on the benefits and challenges faced by GRAPHSEC, and propose a research agenda to advance the AI4SEC domain through GNNs.