Random Number Generators Basedon EEG Non-linear and ChaoticCharacteristics

Abstract

Current electroencephalogram (EEG)-based methods in security have been mainly used for person authentication and identification purposes only. The non-linear and chaotic characteristics of EEG signal have not been taken into account. In this paper, we propose a new method that explores the use of these EEG characteristics in generating random numbers. EEG signal and its wavebands are transformed into bit sequences that are used as random number sequences or as seeds for pseudo-random number generators. EEG signal has the following advantages: 1) it is noisy, complex, chaotic and non-linear in nature, 2) it is very difficult to mimic because similar mental tasks are person dependent, and 3) it is almost impossible to steal because the brain activity is sensitive to the stress and the mood of the person and an aggressor cannot force the person to reproduce his/her mental pass-phrase. Our experiments were conducted on the four EEG datasets: AEEG, Alcoholism, DEAP and GrazA 2008. The randomness of the generated bit sequences was tested at a high level of significance by comprehensive battery of tests recommended by the National Institute of Standard and Technology (NIST) to verify the quality of random number generators, especially in cryptography application. Our experimental results showed high average success rates for all wavebands and the highest rate is 99.17% for the gamma band.

Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation

“…In this system, the random cryptographic key generation includes the selection of features depending on normalized thresholds and the protocol of the segmentation window. Another EEG-based key generation system is proposed by Nguyen D et al 12 . This proposed system indicated that the EEG signal cannot be utilized directly as a source for generating random keys, rather it needs to be transformed before utilizing as random keys generator.…”