UNBUS: Uncertainty-aware Deep Botnet Detection System in Presence of Perturbed Samples. (arXiv:2204.09502v2 [cs.CR] UPDATED)

A rising number of botnet families have been successfully detected using deep
learning architectures. While the variety of attacks increases, these
architectures should become more robust against attacks. They have been proven
to be very sensitive to small but well constructed perturbations in the input.
Botnet detection requires extremely low false-positive rates (FPR), which are
not commonly attainable in contemporary deep learning. Attackers try to
increase the FPRs by making poisoned samples. The majority of recent research
has focused on …

botnet detection system