DDOS attack identification via a silicon photonic Deep Neural Network with 50 GHz input and weight update

Apostolos Tsakyridis, George Giamougiannis, Miltiadis Moralis-Pegios, George Mourgias-Alexandris, Angelina Totovic, George Dabos, Manos Kirtas, Nikolaos Passalis, Anastasios Tefas, Dimitrios Kalavrouziotis, Dimitris Syrivelis, Paraskevas Bakopoulos, Elad Mentovich, Nikos Pleros

Abstract: We experimentally demonstrate distributed denial of service (DDOS) attack identification using Deep Learning over a photonic neuromorphic engine that supports both input signal and weight update at 50 GHz, reporting a Cohen’s κ-score of 0.636.