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Step & Turn is a novel bimodal behavioral biometric-based verification scheme for physical access control. In today’s rapidly evolving smart physical spaces, frictionless and smooth interactions are emerging as critical usability requirements. Such demands need to coexist with mandatory requirements like security. Step & Turn addresses the fundamental limitations of the conventional physical access control schemes, ie, users having a specific knowledge or possessing a particular device or token, to satisfy both usability and security requirements. We design and develop a prototype of Step & Turn by exploiting two natural human behaviors: single footstep and hand-movement to authenticate the users. To evaluate Step & Turn, we design multi-class verification models using three different classifiers. The system achieves a True Acceptance Rate of 97.25% at False Acceptance Rate of 0.01% on a dataset of 1,600 …