Flying drOnes to Locate cyber-attackers in LOraWan Metropolitan nEtworks
Project financed under the call “PRIN: Progetti di ricerca di rilevante interesse nazionale – Bando 2022 PNRR”
ERC field: PE7_8
Project code: P202245HZF
Project CUP: B53D23023810001
“Urban and suburban environments are becoming more and more connected. Internet of Things sensors and actuators are massively present in applications for Smart City, Industry 4.0, Agriculture, Smart Grid, Water and Energy supply.”
“Despite of evident benefits in terms of infrastructure cost savings and mobility, wireless networks are exposed to more cyber-threats than wired links, due to unrestricted access to the transmission medium, tampering of devices in public spaces, and poor design/configuration of the IoT.”
Work Packages
To ensure proper implementation and monitoring of the project, all activities have been framed into 3 technical Work Packages (WPs), while an additional WP will include all management and dissemination activities
WP1 – Scenario and architecture
Led by UNIGE, the aim of the WP is to define the system architecture in order to structure the FOLLOWME solution and define all its components
WP2 – Attacks detection, localization and pursuit
Led by CNR, the WP aims to design and develop the two main components of the FOLLOWME solution and how they are going to interact with each other
WP3 – Integration and validation
Led by UNIGE, the WP focuses on developing the testbed framework to validate the proposed solution
WP4 – Management and dissemination
Led by CNR, the WP covers the management and coordination of the research activity of the involved partners and the dissemination of the obtained achievements
Project partners
Two research partners collaborate to achieve the expected goals of the project
Consiglio Nazionale delle Ricerche (CNR)
Expected project results:
- An ML-based algorithm able to detect cyber-attacks affecting LoRAWAN networks and sensors (IDS component), released as software code
- An incident response procedure specifically designed for the FOLLOWME scenario, to manage the incident once it is detected, by triggering both the UAV and the response team
Università degli Studi di Genova (UNIGE)
Expected project results:
- An algorithm able to localize the attacker based on information collected both by the network ground station(s) and the deployed UAV (localizer component), released as software code
- A UAV prototype consisting in the selected UAV and the LoRaWAN hardware components to let it contribute to the attacker localization task. The prototype will be designed asa modular solution to let the LoRaWAN onboard componentsbe installed on different drones as well
Project deliverables
| Number | Name | Delivery month | Delivery date | Dissemination level | Leader |
| D1 | FOLLOWME state of the art and architecture | M8 | 29/07/2024 | Confidential | CNR |
| D2 | FOLLOWME detection, localization and pursuit | M16 | 29/03/2025 | Confidential | CNR |
| D3.1 | FOLLOWME software release | M22 | 29/09/2025 | Confidential | UNIGE |
| D3.2 | FOLLOWME validation | M24 | 29/11/2025 | Confidential | UNIGE |
| D4.1 | FOLLOWME dissemination – Initial | M12 | 29/11/2024 | Confidential | CNR |
| D4.2 | FOLLOWME dissemination – Final | M24 | 29/11/2025 | Confidential | CNR |
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