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Privacy and Security by Design in Brain-Computer Interfaces

In this research project, we propose that elements of users' electro-physiological signals can be used to extract private information about them. This hypothesis is being tested using non-invasive brain-computer interfaces (BCIs). We are also developing a signal processing mechanism to prevent this type of privacy threat.

The problem

A BCI is a communication system between the brain and the physical environment. Recent experimental results show how electroencephalograms (EEG), obtained using consumer-grade BCIs, can be used to extract private information about users. This information can be exploited and misused to infer about users’ memories, intentions, conscious and unconscious interests, as well as emotional responses. Privacy and security issues arising from the misuse of BCIs represent an emerging problem that deserves careful consideration.

 
Privacy and Security by Design in BCIs

Our solution

The goal of this project is to make improvements in the privacy and security of BCI-enabled technologies. In doing so, the project consists of two major steps. The focus of the first step is identification of components of the recorded neural signals that can be used to extract private information, and the quantification of the amount of exposed information. Based on the obtained results, the focus of the second step is the development, analysis and validation of a tool  to enhance privacy and security properties of BCIs, which we refer to as the BCI Anonymizer. It is a signal processing tool that decomposes users' signals into components, in order to grant access to the information corresponding to users' intended BCI commands while preventing anyone from accessing their' private information. 

Impact

The aims of this project are expected to enhance the development of the closed-loop brain-controlled interfaces. The knowledge of how to extract private information from the recorded electro-physiological signals, and more importantly, how to decompose recorded signals to prevent the potential private information leakage, will advance the ability to select useful control commands from the brain in real time. Moreover, as more BCIs start involving wireless communication, this project will provide enabling technology for addressing the emerging security and privacy issues.

Acknowledgments

 
National Science Foundation
 
Center for Sensorimotor Neural Engineering