Machine Learning based Classification System to detect tampered Big Data in the context of a Simulated Aqueduct

In order to secure data of an Aqueduct, a simulated environment has been developed inside the Cyber Range in Superior Institute Mario Boella. The object of this thesis is to create and compare Classification algorithms based on Machine Learning which best fits the proposed model. This Classifier, trained only using "true" class data, should recognize tampered data caused by anomalies or malevolent attackers.