Explainable Intrusion Detection Systems Using Competitive Learning Techniques. (arXiv:2303.17387v1 [cs.CR])

The current state of the art systems in Artificial Intelligence (AI) enabled
intrusion detection use a variety of black box methods. These black box methods
are generally trained using Error Based Learning (EBL) techniques with a focus
on creating accurate models. These models have high performative costs and are
not easily explainable. A white box Competitive Learning (CL) based eXplainable
Intrusion Detection System (X-IDS) offers a potential solution to these
problem. CL models utilize an entirely different learning paradigm than …

art artificial artificial intelligence black box box competitive current detection error family focus high ids intelligence intrusion intrusion detection intrusion detection system paradigm problem process solution state system systems techniques