Real-time stream processing tool for detecting suspicious network patterns using machine learning
Mikołaj Komisarek, Michał Choraś, Rafał Kozik, Marek Pawlicki · 2020
In this paper, the performance of stream processing and accuracy in the prediction of suspicious flows in simulated network traffic is investigated. In addition, concepts of an engine that integrates with novel solutions like the Elastic-search database and Apache Kafka that allows easy definition of streams and implementation of any machine learning algorithm are presented.