Security Assessments of Data Transfer Phase of Adapted EEG System in Learning Systems

Electroencephalography (EEG) is a method used to record electrical activity in the brain. The output of electrical activity can have a wide range of benefits. As an example, it can reflect an individual's perception of stress, happiness, fear, or focus. Thus, in online labs, students can receive content that can be customized according to their level of focus. In this case, the EEG data that can be obtained from students in online laboratories can easily be used to create dynamic presentation content, performance highlights, or continuous feedback from the instructor. However, security assessments of EEG devices during the data acquisition and transmission phases will increase confidence in the aforementioned benefits. This paper presents the details and experimental results of cyber-attacks on EEG data that could potentially be used in online laboratories. In this study, methods such as machine learning (ML), replay, and man-in-the-middle attack are targeted at EEG devices and the results are presented.