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AUTOSAR's transformers and MQTT for a fast and secure communication between cars and external networks

Alessandro Salvatore

AUTOSAR's transformers and MQTT for a fast and secure communication between cars and external networks.

Rel. Edgar Ernesto Sanchez Sanchez. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2022

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As our cars become more and more complex, so do the computer systems that manage them and keep them under control. In the near future, communications from the embedded systems within cars to external networks will become more and more indispensable. This kind of communications, called "Car-to-X", have endless use cases: signalling system faults and incidents to a road operator, communicate between cars to manage the traffic, telling crossing cyclists that a vehicle is approaching and so on. Currently the most widespread standard for automotive embedded systems software, AUTOSAR, does not natively support a standardized way of achieving a fast and secure architecture for communicating with an external network. I started an internship at Brain Technologies, during which I implemented such an architecture using AUTOSAR's transformers and the MQTT protocol: the former helped me develop an easy way to ensure confidentiality, integrity and data origin authentication of the messages exchanged; the latter was used to send such messages to an external server in the most secure way given the time restrictions of a running car. This thesis serves as a compendium to all the work carried out during the internship. It starts with an overview of all the standards and the technologies used; then it proceeds with a description of some use cases of the projects and the environment where it was developed; lastly it ends with an in-detail explanation of the architecture and a look on possible future developments.

Relators: Edgar Ernesto Sanchez Sanchez
Academic year: 2021/22
Publication type: Electronic
Number of Pages: 91
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: Brain technologies
URI: http://webthesis.biblio.polito.it/id/eprint/22657
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