Bridging the gap to real-world for network intrusion detection systems with data-centric approach

1 code implementation • 25 Oct 2021 • Gustavo de Carvalho Bertoli, Lourenço Alves Pereira Junior, Filipe Alves Neto Verri, Aldri Luiz dos Santos, Osamu Saotome

Most research using machine learning (ML) for network intrusion detection systems (NIDS) uses well-established datasets such as KDD-CUP99, NSL-KDD, UNSW-NB15, and CICIDS-2017.

BIG-bench Machine Learning Network Intrusion Detection

Feature learning in feature-sample networks using multi-objective optimization

no code implementations • 25 Oct 2017 • Filipe Alves Neto Verri, Renato Tinós, Liang Zhao

We show that the enhanced network contains more information and can be exploited to improve the performance of machine learning methods.

BIG-bench Machine Learning

Network Unfolding Map by Edge Dynamics Modeling

no code implementations • 3 Mar 2016 • Filipe Alves Neto Verri, Paulo Roberto Urio, Liang Zhao

Labeled vertices generate new particles that compete against rival particles for edge domination.