CRMar 24, 2017

Secure Management of Low Power Fitness Trackers

arXiv:1703.08455v158 citations
Originality Incremental advance
AI Analysis

This addresses security risks for users of affordable fitness trackers, but it is incremental as it builds on existing reverse-engineering and protocol design methods.

The paper tackled security vulnerabilities in popular fitness trackers (Fitbit Ultra and Garmin Forerunner 610) by reverse-engineering them and introducing attacks, and it resulted in SensCrypt, a protocol that thwarts these attacks and reduces sync overhead on a low-cost tracker platform.

The increasing popular interest in personal telemetry, also called the Quantified Self or "lifelogging", has induced a popularity surge for wearable personal fitness trackers. Fitness trackers automatically collect sensor data about the user throughout the day, and integrate it into social network accounts. Solution providers have to strike a balance between many constraints, leading to a design process that often puts security in the back seat. Case in point, we reverse engineered and identified security vulnerabilities in Fitbit Ultra and Gammon Forerunner 610, two popular and representative fitness tracker products. We introduce FitBite and GarMax, tools to launch efficient attacks against Fitbit and Garmin. We devise SensCrypt, a protocol for secure data storage and communication, for use by makers of affordable and lightweight personal trackers. SensCrypt thwarts not only the attacks we introduced, but also defends against powerful JTAG Read attacks. We have built Sens.io, an Arduino Uno based tracker platform, of similar capabilities but at a fraction of the cost of current solutions. On Sens.io, SensCrypt imposes a negligible write overhead and significantly reduces the end-to-end sync overhead of Fitbit and Garmin.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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