HomeScout: A modular Bluetooth Low Energy Sensing App

This project focuses on Bluetooth Low Energy (BLE) devices and cross-platform app development. Since Apple's AirTag release, there has been continuous interest in the tracker's ability to protect users' privacy and protect them from being spied on or stalked [1, 2].

Nevertheless, this opens up the world to many other scenarios, where any BLE device can be either attached to Apple's Find My network [4] or utilized on its own to track a person, their habits, and location. Therefore, an application that tracks any BLE devices that come in contact with the user's smartphone both on the go and in a smart home environment is beneficial. This work focuses on:

• The identification of passively scanned BLE devices 
• Extraction of key data points from scanning results
• The design and prototyping of the categorization/classification of these BLE devices
• E.g. into type of smart home devices [5]
• E.g. scoring of this information to ascertain a security score [6]
• Persistence of information onto a Raspberry Pi MongoDB database

Since design is a key element of this work, there is a degree of freedom in deciding how to approach the problem and how to implement the solution.

Project Question: What BLE information is necessary to identify a specific BLE device?  What would be the best way to categorize or classify said devices into groups or types? How can we score the gathered information according to privacy or security requirements? 

[1] https://eu.usatoday.com/story/tech/2022/02/10/apple-airtags-privacy-update-stalking/6738071001/

[2] https://www.bbc.com/news/technology-60004257

[3] https://tidbits.com/2021/05/15/13-airtag-tracking-scenarios/

[4] https://github.com/seemoo-lab/openhaystack#finding-3

[5] https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/ntw2.12007

[6] http://personales.upv.es/thinkmind/dl/conferences/securware/securware_2019/securware_2019_6_20_30082.pdf