1 code implementation • 22 Jan 2024 • Andrea Corsini, Angelo Porrello, Simone Calderara, Mauro Dell'Amico
Inspired by Semi- and Self-Supervised learning, we show that it is possible to easily train generative models by sampling multiple solutions and using the best one according to the problem objective as a pseudo-label.
1 code implementation • 28 Aug 2023 • Andrea Corsini, Shanchieh Jay Yang
Our findings suggest that existing detectors can identify a consistent portion of new malicious traffic, and that improved embedding spaces enhance detection.
no code implementations • 7 Jul 2022 • Andrea Corsini, Simone Calderara, Mauro Dell'Amico
Finally, we empirically demonstrate the value of predicting the quality of machine permutations by enhancing the performance of a simple Tabu Search algorithm inspired by the works in the literature.
no code implementations • 15 Jun 2021 • Andrea Corsini, Shanchieh Jay Yang, Giovanni Apruzzese
Recent advances in deep learning renewed the research interests in machine learning for Network Intrusion Detection Systems (NIDS).