Bluetooth Low Energy Communication Security in Wearable IoT Devices: A Fitbit Sense 2 Case Study
Year: 2026
Type: conference-paper
Abstract: Wearable devices have become an integral component of the Internet of Things (IoT) ecosystem, continuously collecting and transmitting sensitive biometric and personal data through wireless communication protocols. Many of these devices rely on Bluetooth Low Energy (BLE) to enable energy-efficient communication between wearable sensors, smartphones, and cloud services. Despite its widespread adoption, concerns remain regarding the security and privacy of BLE communications within wearable IoT systems. This study presents an experimental security assessment of BLE communications in the Fitbit Sense 2 wearable device. A controlled penetration testing environment was established using Kali Linux, Ubertooth One, and Wireshark to analyze BLE packet transmissions and broadcast behavior under both normal and anomalous connection conditions. The experiments evaluated the visibility of transmitted packets and the effectiveness of previously reported GATT fingerprinting techniques used to identify BLE traffic. Results indicate that recent firmware updates have improved resistance to traditional packet sniffing techniques through enhanced packet obfuscation and reduced broadcast fingerprint visibility. However, the experiments also revealed an anomalous persistent connection behavior in which the device continues to receive notifications despite appearing disconnected from the host smartphone, potentially exposing user data without clear user awareness. These findings highlight both the progress and remaining challenges in securing BLE communications within wearable IoT devices and underscore the need for further investigation of communication protocol behaviors that may impact user privacy and system security.
Institution: University of South Carolina Aiken
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7204242416