Abstract
The rapid evolution of network infrastructure through the softwarization of network elements has led to an exponential increase in the attack surface, thereby increasing the complexity of threat protection. In light of this pressing concern, European Telecommunications Standards Institute (ETSI) TeraFlowSDN (TFS), an open-source microservice-based cloud-native Software-Defined Networking (SDN) controller, integrates robust Machine-Learning components to safeguard its network and infrastructure against potential malicious actors. This work presents a comprehensive study of the integration of these Machine-Learning components in a distributed scenario to provide secure end-to-end protection against cyber threats occurring at the packet level of the telecom operator’s Virtual Private Network (VPN) services configured with that feature. To illustrate the effectiveness of this integration, a real-world emerging attack vector (the cryptomining malware attack) is used as a demonstration. Furthermore, to address the pressing challenge of energy consumption in the telecom industry, we harness the full potential of state-of-the-art Green Artificial Intelligence techniques to optimize the size and complexity of Machine-Learning models in order to reduce their energy usage while maintaining their ability to accurately detect potential cyber threats. Additionally, to enhance the integrity and security of TeraFlowSDN’s cybersecurity components, Machine-Learning models are safeguarded from sophisticated adversarial attacks that attempt to deceive them by subtly perturbing input data. To accomplish this goal, Machine-Learning models are retrained with high-quality adversarial examples generated using a Generative Adversarial Network.
Alberto Mozo
Head of the research group
Full professor
I am a Full Professor at the Technical University of Madrid (Universidad Politécnica de Madrid) and lead the Research Group on Mathematical Modeling and Biocomputing at the same institution.
Amit Karamchandani
Predoctoral Researcher
Amit Karamchandani Batra, a predoctoral researcher and Ph.D. student at the Universidad Politécnica de Madrid, has contributed to EU-funded 5G cybersecurity projects, co-authored research papers, and received multiple academic awards, including for his B.Sc. and M.Sc. degrees.
Luis de la Cal
Predoctoral researcher
I’m a PhD candidate focused on smart cities, collective intelligence, and innovative technologies like augmented reality and biosensors, with experience in research and entrepreneurship.