Cyber Attack Drone Payload Development and Geolocation via Directional Antennae
Abstract
Commercial drones have made amazing improvements in flight time, flight distance, and payload weight. These same features also offer a unique and unprecedented commodity for wireless hackers the ability to gain physical proximity to a target without personally having to be near it. This thesis experimentally evaluates the ability of a drone-based attack system to track its targets by passively sniffing Wi-Fi signals from distances of 300 and 600 meters using a directional antenna. Additionally, it identifies collection techniques and processing algorithms for minimizing geolocation errors. This research also develops "skypie," a software/hardware framework designed for performing remote, directional drone-based collections. The prototype simulates a device that can be built by a motivated threat actor. This research evaluates strengths and shortcomings posed by these devices. This research ultimately assists in developing operational drone-borne cyber-attack and reconnaissance capabilities while also enlightening the public of countermeasures to mitigate the privacy threats posed by the inevitable rise of the cyber-attack drone.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 21, 2019
- Accession Number
- AD1074625
Entities
People
- Clint M. Bramlette
Organizations
- Air Force Institute of Technology