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  KEYWORD

EDA Group

Advanced network analysis techniques and self-learning for recognition of network traffic anomalies.

azienda Thesis in external company    


keywords MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS

Reference persons ALESSANDRO ALIBERTI, EDOARDO PATTI

External reference persons Alessio Viticchié

Research Groups DAUIN - GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, EDA Group, ELECTRONIC DESIGN AUTOMATION - EDA, Energy Center Lab, GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ICT4SS - ICT FOR SMART SOCIETIES

Thesis type APPLIED RESEARCH

Description In the context of a company project (DIANA), the student will investigate the state of the art about Machine Learning techniques for network traffic analysis for automatic modelling

The thesis will be divided into two main phases:
Analysis of industrial network traffic to define reference models for normal traffic and anomalies.
Implementation of machine learning algorithms capable of recognizing the anomalies detected in network traffic and reporting any security threats

Expected results:
The thesis aims to develop an effective methodology for analyzing industrial systems through network traffic analysis. The model created through reverse engineering will allow the identification of system vulnerabilities and potential security threats, enabling security operators to take preventive measures to protect the industrial plant. Additionally, the thesis will contribute to the understanding of communication protocols used in industrial plants, allowing for the development of more effective and targeted security solutions.


Deadline 13/03/2024      PROPONI LA TUA CANDIDATURA