A Review Study of Brian Activity-Based Biometric Authentication

Abstract

Biometrics is the process of identifying an individual among others by biological means. Concerning security, biometric system is one of the best options available in this technology driven era. Places such as nuclear facilities, airports, banks etc. are on the frontline of security threats. Therefore, biometrics such as Iris, face and fingerprint recognition is frequently used to avoid any security breach. However, the possibility of imitating, replicating or even the stealing of original data has made these tools unreliable. As a result, there has been a growing interest in finding a better biometric system and brain activitybased biometrics such as Electroencephalography (EEG) and Functional Near-Infrared Spectroscopy (fNIRS) come with the advantage of being quite impossible to mimic. This paper presents a thorough and in depth review of the state of the art studies and research on brain activity-based biometrics. These studies and selected research projects are reviewed based on their feature extraction, methods, classification and most importantly, performance. Reviewing the most recent studies and research, we have found that time and frequency based features are better to be considered together for a brain activity-based biometric system. Together they are effective and efficient and give us a higher performance rate. Furthermore, we have found that Support Vector Machine (SVM) classifier is the best classification option with 100% accuracy and it can be used for a higher number of users for a biometric system. Our review lays a foundation for future investigation into the use of a combination of EEG and fNIRS for a biometric based authentication system.

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

“…As a result, there has been a growing interest in finding a better biometric system and brain activity-based biometrics. An EEG system-based biometric has been identified to have the advantage of being quite impossible to mimic (Alariki et al, 2018). Using 15 human participants, Ruiz Blondet et al (2015) studied the stability of EEG brainwaves over a 6-month period.…”

“…However, it is worth mentioning that the content of the review emphasized and was restricted to only BCI spellers. There are other notable BCI reviews that cater to specific applications, for instance, wheelchair control (Fernández-Rodríguez et al, 2016;Al-qaysi et al, 2018), BCI mobile robot (Bi et al, 2013), emotion recognition using EEG (Al-Nafjan et al, 2017), biometrics (Del Pozo-Banos et al, 2014;Alariki et al, 2018), and virtual reality and gaming (Kaplan et al, 2013;Ahn et al, 2014;Cattan et al, 2018). Nevertheless, some pertinent information was missing or not duly reported, for instance, descriptions of methodology and evaluation metrics employed, and/or future directions of the research.…”

Confirmation of Personality Types Using Visual Evoked Potential with User Interface Design Stimulus

“…Electroencephalogram (EEG) is the transcription of an electrical for brain activity, described as voltage fluctuations generating from ionic currents in the neuronal brain (Niedermeyer and Silva, 2005). Researches with EEG used for biometric aims are increasing in use for personal recognition purpose (Alariki et al, 2018). User interface development made use of EEG has been developed to validate design acceptance (Bang et al, 2011).…”

Toward EEG-Based BCI Applications for Industry 4.0: Challenges and Possible Applications

“…However, recent advances in neuroscience and technology, especially non-invasive and portable brain imaging techniques related to EEG, have encouraged the development of novel applications outside the medical and scientific areas (e.g., Abdulkader et al, 2015;Rashid et al, 2020). Notably, one might list the following fields of education (e.g., Wegemer, 2019), entertainment (e.g., Bonnet et al, 2013;Kerous et al, 2018;Ramchurn et al, 2018;Vasiljevic and Miranda, 2020), biometrics authentification (e.g., Alariki et al, 2018;Chan et al, 2018), or even civil and military aviation (e.g., Dehais et al, 2018).…”