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

Marco Zanobini

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

Rel. Paolo Ernesto Prinetto. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2019

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Abstract:

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.

Relators: Paolo Ernesto Prinetto
Academic year: 2018/19
Publication type: Electronic
Number of Pages: 86
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/11058
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