An Artificial Immune System for Identifying people using EEG

An Electroencephalogram (EEG) is the recording of electrical activity from the surface of the brain. It is proved that there is a significant amount of individuality in the EEG signals, accordingly its can be treated as a biometric feature for an individual and used for human identification. In this paper, we present an artificial immune system for identifying users using EEG signals; we conducted an experiment for user identification. In the experiment the user is asked to perform a set of tasks while multiple sensors are attached to them. The sensors capture the EEG, EMG, ECG, GSR signals from the subject during the experiment. The user is asked to perform several tasks during the experiment which includes reading transcriptional typing and hacking a password. After all the data is captured, the signal is cleaned and we use artificial immune systems (AIS) algorithms to match system users. Key-Words: EEG, Brain, AIS, negative selection, identification, biometrics, negative selection, positive selection