A New Security Mechanism for IoT Devices: Electroencephalogram (EEG) Signals

The variety and high usage rate of Internet of Things (IoT) devices make them a prime target for cyber-attacks. Unfortunately, the limited physical size of IoT devices prevents the use of powerful computing components to secure these devices with sophisticated encryption methods. Hence, typically, symmetric-asymmetric, lightweight, and hybrid methods are used to secure IoT devices. However, each of these approaches has its disadvantages; thus, none of them is considered successful in preventing cyber-attacks on IoT devices. On the other hand, security procedures based on biological uniqueness can be effective in solving this predicament of IoT devices. While biological singularity methods such as fingerprint and facial recognition systems are also utilized to secure IoT devices, technological innovations such as artificial intelligence and deepfake still lead to vulnerabilities in IoT. Nonetheless, because of the uniqueness of the biological singularity, here, we present a mechanism to secure such devices that combines the encryption and the human factor while minimizing the possible attack surface to the system. Specifically, in this paper, we propose the use of users’ brain frequencies as a security mechanism in IoT devices. The work showed that obtained data from AF3-Pz-T8-AF4 electrodes can be used to secure IoT devices.