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 thigh-lift), 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.

我们提出了一种新颖的对抗模型，用于使用智能手机内置的惯性测量单元（IMU）记录的步态模式进行身份验证系统。该模型探索了构建 IMUGait 模式字典并使用其发起攻击或找到能够主动重现与目标的 IMUGait 模式匹配的模仿者是否可能。