Spatiotemporal security in mixed reality systems

Abstract

This paper exhaustively explores the threat landscape of coordinated spatiotemporal attacks in mixed reality systems. Novel devicelevel and cross-device time translation and spatial shift attacks are launched, and their impact on deep learning based sensor fusion is evaluated. A major focus of this work is to establish stealthiness in the presence of sophisticated security mechanisms with an added constraint that mixed reality systems allow minimal time durations for covert operation. The efficacy of proposed attacks is evaluated through a preliminary study on inertial and visual data streams.