Summary

ECU-IoFT (Edith Cowan University) documents three known cyber-attacks targetting Wi-Fi communications and lack of security in an affordable off-the-shelf drone.

• Denial-of-service (control signals and GPS)
• Man-in-the-middle attacks
• Exploited API

IoFT - Internet of Flying Things

No publicly available labeled datasets that reflect cyberattacks on IoFT.

Publicly available network traffic datasets are emulated and not real test setup.

Creates dataset targeting Ryze Tello Drone

Dataset: ECU-IoFT Dataset

Contribution

• Cyber vulnerability analysis of an off-the-shelf low-cost drone used in educational purpose.
• Risk associated of using vulnerable drones.
• Simulation of three cyber attacks on IoFT scenario.
• Development of benchmark dataset capturing network traffic.
• Performance analysis of most popular anomaly detection algorithms using developed dataset.
• Future research directions of IoFT cyber security.

Dataset Development

a purpose-made IoFT dataset needs to be created to adequately identify security threats targeted by Low-end consumer IoFT devices, often used within the education sector.

Development followed the remote grey box penetration test philosophy

• Penetration test is considered a grey box when some but not all of the information and internal workings of the target is known.
• Eg. Knowing the drone being targeted without knowledge of inner workings.

Pre-engagement -> Information gathering -> Threat modeling -> Vulnerability analysis -> Exploitation -> Post exploitation -> Reporting

Environment

• Ryze Tello TLW004 running firmware version 01.04.92.01.
• UAV controlled via Google Pixel 2 - Android 10 (QQ3A.200805.001) - Tello app (1.6.0.0).
• Attack machine running Kali Virtual Machine build 2021.2 within VMware Workstation Pro 16.1.2.

Attacks

• Wi-Fi Deauthentication Attack.
• WPA2-PSL Wi-Fi Cracking Attack.
• Tello API Exploit.

Evaluation

It is drone type dependent, so collection and testing with other drones is also required.