PORTALE DELLA DIDATTICA

Ricerca CERCA
  KEYWORD

Secure Edge-Computing exploiting Artificial Intelligence Applications

keywords ARTIFICIAL INTELLIGENCE, EDGE COMPUTING, EMBEDDED SYSTEMS, IOT, IOT PROTOCOLS, NETWORK SECURITY, SECUBE, SECURE EDGE COMPUTING, SECURITY

Reference persons PAOLO ERNESTO PRINETTO

External reference persons Nicolò MAUNERO (CINI Cybersecurity National Laboratory)
Gianluca ROASCIO (CINI Cybersecurity National Laboratory)
Antonio VARRIALE (Blu5 Labs Ltd)

Research Groups GR-21 - TESTGROUP - TESTGROUP

Thesis type MASTER THESIS

Description The increased usage of IoT devices at the edge of the network is producing a massive amount of data to be computed at data centers, pushing network bandwidth requirements to the limit. The aim of the so-called Edge Computing paradigm is to move the computation away from data centers towards the edge of the network, exploiting smart objects, mobile phones or network gateways to perform tasks and provide services on behalf of the cloud. Thus, not only data centers are offloaded, but also improvements are achieved in terms of scalability, reliability, efficiency and also security.
SEcube™ is a chip developed by Blu5® as an Open Security Platform. The chip is a 3D SiP (System-in-Package) containing a STMicroelectronics processor, a little FPGA and a smart card (www.secube.eu). Thanks to its security capabilities and the possibility of using a reconfigurable hardware, the chip is perfectly suited to the demands of the Edge Computing paradigm.
The aim of the thesis is therefore to develop a real-life application running on SEcube™ that resorting to machine learning algorithms secure at-the-edge by detecting anomaly in the communication with IoT sensors. The algorithms can be implemented in software and/or in hardware, exploiting the internal FPGA.


External/Industrial cooperations:
- Blu5® Labs Ltd (Malta)
- CINI Cybersecurity National Laboratory

Notes The thesis activities will be carried out in collaboration with:
- Blu5 Labs Ltd (Malta)
- CINI Cybersecurity National Laboratory

For additional information:
- Nicolò MAUNERO – nicolo.maunero@polito.it
- Gianluca ROASCIO – gianluca.roascio@polito.it


Deadline 31/12/2022      PROPONI LA TUA CANDIDATURA




© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti