Dictionary Attack on IMU-based Gait Authentication
16th ACM Workshop on Artificial Intelligence and Security
We present a novel adversarial model for authentication systems that use gait patterns recorded by the inertial measurement unit (IMU) built into smartphones. The attack idea is inspired by and named after the concept of a dictionary attack on knowledge (PIN or password) based authentication systems. In particular, this work investigates whether it is possible to build a dictionary of IMUGait patterns and use it to launch an attack or find an imitator who can actively reproduce IMUGait patterns that match the target’s IMUGait pattern. Nine physically and demographically diverse individuals walked at various levels of four predefined controllable and adaptable gait factors (speed, step length, step width, and thighlift), producing 178 unique IMUGait patterns. Each pattern attacked a wide variety of user authentication models. The deeper analysis of error rates (before and after the attack) challenges the belief that authentication systems based on IMUGait patterns are the most difficult to spoof; further research is needed on adversarial models and associated countermeasures.
Code and dataset available in Github
Rajesh Kumar, Can Isik, and Chilukuri Krishna Mohan. 2023. Dictionary Attack on IMU-based Gait Authentication. In Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security (AISec ’23), November 30, 2023, Copenhagen, Denmark. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3605764.3623909