Bluetooth-based Tracking Devices: Extraction and Analysis of Digital Forensic Artifacts from Android Applications
Name
Md. Rashadul Islam
Abstract
The extraction and analysis of data from user applications installed on mobile devices is the subject of mobile forensics, a rapidly expanding subfield of digital forensics. The need for digital forensics is becoming increasingly apparent with the smartphone market’s accelerated expansion and the IoT device industry’s rising innovation. IoT devices are, therefore, compatible with smartphones and have become essential. Mobile phones are typically owned by a single individual, making them a valuable source of personal data for forensic examination. Depending on the company’s technology and the environment, these Bluetooth tracking devices, widely known as Bluetooth beacons (transmitters), can be linked with the mother device and broadcast positions to their identifier within the range. This beacon uses BLE to transmit a UUID picked by an application or operating system. When it is used with a smart device with a beacon as a tracker application, it can save additional user data with the aid of a user application through Bluetooth and a Wi-Fi or internet connection. As a result, smartphones can serve as a source of forensic evidence when there is a case file about a stalking attack or cyberstalking in court. Therefore, we will examine what artifacts can be gleaned from Bluetooth tracking apps and whether this information can be used as evidence. Based on Android Bluetooth (BLE) trackers, including the Smart Tag Plus, HTC Fetch, Chipolo Classic, and Tile Slim for Samsung Galaxy A13 devices, we analyzed four Bluetooth tracking applications to demonstrate the potential artifacts obtained and how the data extraction approach was carried out. We also suggest which extraction technique is most important for an inquiry to bring more artifacts. Finally, we give a flowchart of our steps to gather information from a Bluetooth-based tracking device.
Graduation Thesis language
English
Graduation Thesis type
Master - Cyber Security
Supervisor(s)
Hayretdin Bahsi; Raimundas Matulevičius
Defence year
2024