Artificial intelligenceNetwork engineeringSecurity research
Research Fields
Project Summary
In today`s digital age, the rise of cybercrime poses a significant threat to our online
security. The GRAPHS4SEC research project aims to revolutionize the way we protect
our networks using cutting-edge technology known as Graph Neural Networks (GNNs).
Traditional methods of using Artificial Intelligence (AI) and Machine Learning (ML) for
network security have fallen short. They struggle to adapt, perform poorly in real-world
situations, and are susceptible to cyber-attacks. The primary reason for these
limitations is the lack of specialized AI/ML technology designed specifically for network
security challenges.
At GRAPHS4SEC, the spotlight is on harnessing the potential of GNNs to enhance
cybersecurity. These are advanced systems that excel at understanding and learning
from interconnected information, perfect for the relational nature of network security
data. Imagine them as digital detectives for our online safety.
The project has three main goals:
Smart AI-powered Cybersecurity Algorithms: we will explore new ways to model and
learn from network security data using graph-based approaches. This means creating
smart algorithms that understand the complex relationships within cybersecurity
information.
Understanding the Added Value: the team will compare how well GNN-based
approaches perform against traditional AI/ML methods. This involves evaluating
detection capabilities, adaptability, scalability, and resilience against cyber threats. It`s
like putting the new technology to the test to see if it outperforms the old.
Real-World Cybersecurity Applications: the ultimate aim is to apply GRAPHS4SEC
technology in real-world scenarios. For that, will focus on four critical areas of
cybersecurity, with a special emphasis on the detection and early mitigation of phishing
and malicious websites, a pervasive and significant threat that poses widespread harm
in today`s digital landscape.
In essence, GRAPHS4SEC strives to create a new generation of powerful, resilient,
and effective AI-driven cybersecurity tools. By harnessing the unique capabilities of
GNNs, the project aims to enhance our ability to safeguard against cyber threats and
make the online world a safer place for everyone.
Research Outputs (6)
publications (6)
Title
Year(s)
DOI / Link
TSGFM - Graph Neural Networks for Zero-Shot Time Series Forecasting in Network Monitoring