Emotional Influences on Cryptographic Key Generation Systems using EEG signals
Dang Nguyen, Dat Thanh Tran, Dharmendra Kumar Sharma, Wanli Ma · Procedia Computer Science · 2018
This paper presents a research conducted to verify the influences of emotion on electroencephalogram (EEG)-based cryptographic key generation system. Emotion, such as negative and positive feelings, involves in EEG signal, and hence it may influence on the system. This issue has not been analyzed. Using parametric spectral estimation technique for feature extraction, and devised a quantization technique for error correction, a key is generated from EEG data. These techniques are believed to be suitable for a noisy data such as EEG. For experiment implementation, we use the Database for Emotion Analysis using Physiological Signals (DEAP) dataset. The emotional dimensions used are valence (positive and negative) and arousal (calm and excited) that is divided each in two classes: low and high. For experimental methodology, we performed on two groups of subjects, valence and arousal. Experimental results show that emotion actually has impacts on the performance of the system.