Back to results

Syracuse University

Treadmill Assisted Circumvention of Wearable Sensors-based Gait Authentication

Abstract

dc:description.abstract

<p>Wearable sensor-based gait patterns are considered a promising means for future authentication systems. This dissertation examines whether circumvention of such systems can be accomplished by imitating sensor readings and providing external mechanical support. The specific machine that we used in the experiment was a digital treadmill, which provides a suitable platform for the human imitators to control, adjust and adapt several factors, such as speed, step-length, step-width, and thigh-lift that affect sensor readings. Moreover, it was easy for imitators to remember the gait factors' specific levels and repeat the learned pattern on-demand over a treadmill. </p><p>Two novel imitation-based attacks are explored in our work. The first harnesses the power of feedback loops, widely studied for regulating human behavior. The second utilizes the dictionary-based approach, successfully used to defeat password-based authentication systems. We also discuss how the proposed techniques apply to other authentication systems.</p><p>The effectiveness of the proposed techniques was evaluated on a newly created dataset of fifty-five genuine users and nine carefully chosen imitators. A series of user-specific authentication systems were developed and tested under zero-, dictionary-, and high-effort imitation environments. Our experimental findings suggest that adversarial samples generated with a treadmill's assistance can help circumvent wearable sensors-based gait authentication systems, necessitating reconsideration of their use in high-security environments. In the end, we discuss several possible countermeasures that would help mitigate the presented attack.</p>

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (PhD)
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Electrical Engineering and Computer Science
Year
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kumar, Rajesh
Contributors dc:contributor
  • Mohan, Chilukuri K.
  • Isik, Can

Subjects

dc:subject × 10

Identifiers

dc:identifier.*
Repository record dc:identifier
https://surface.syr.edu/etd/1530
OAI identifier oai:identifier
oai:surface.syr.edu:etd-2531

Chain of custody

source
Harvested from
Syracuse University
Base URL
surface.syr.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Kumar, Rajesh. Treadmill Assisted Circumvention of Wearable Sensors-based Gait Authentication. Dissertation thesis, 2021. https://surface.syr.edu/etd/1530