Majed Jaber

In Rencontre des jeunes chercheurs en inteligence artificielle (RJCIA-2023)

Abstract At this time, cyberattacks represent a constant threat. Many approaches exist for detecting suspicious behaviors, but very few of them seem to benefit from the huge potential of mathematical approaches like spectral graph analysis, known to be able to extract topological features of a graph using its Laplacian spectrum. For this reason, we consider our network as a dynamic graph composed of nodes (representing the devices) and of edges (representing the requests), and we compute its Laplacian spectrum across time.

Towards attack detection in traffic data based on spectral graph analysis

By Majed Jaber, Nicolas Boutry, Pierre Parrend

2023-04-01

Abstract Nowadays, cyberattacks have become a significant concern for individuals, organizations, and governments. These attacks can take many forms, and the consequences can be severe. In order to protect ourselves from these threats, it is essential to employ a range of different strategies and techniques like detection of patterns, classification of system behaviors against previously known attacks, and anomaly detection techniques. This way, we can identify unknown forms of attacks. Few of these existing techniques seem to fully utilize the potential of mathematical approaches such as spectral graph analysis.

Structural and spectral analysis of dynamic graphs for attack detection

Towards attack detection in traffic data based on spectral graph analysis

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