Adversarial Stimuli: Attacking Brain-Computer Interfaces via Perturbed Sensory Events. (arXiv:2211.10033v1 [cs.CR])

Machine learning models are known to be vulnerable to adversarial
perturbations in the input domain, causing incorrect predictions. Inspired by
this phenomenon, we explore the feasibility of manipulating EEG-based Motor
Imagery (MI) Brain Computer Interfaces (BCIs) via perturbations in sensory
stimuli. Similar to adversarial examples, these \emph{adversarial stimuli} aim
to exploit the limitations of the integrated brain-sensor-processing components
of the BCI system in handling shifts in participants' response to changes in
sensory stimuli. This paper proposes adversarial stimuli as an …

adversarial brain computer events sensory