Volume 2 - Issue 1, January - February 2026

The growing pace of digital systems has led to the exposure of traditional methods of authentication, like passwords and biometric identifiers, to mounting levels of concerns of safety, privacy, and vulnerability to impersonation attacks[1]. To counter these limitations, this paper proposes a brainwave-based secure authentication mechanism that makes use of distinct neural identity sensitivity on electroencephalographic (EEG) responses[2]. The suggested model focuses on four main EEG frequency bands such as delta, theta, alpha and beta, which represent the unique cognitive and physiological features of individual subjects[3]. The features are received through signal preprocessing and feature extraction algorithms and then categorized through the use of a Gradient Boosting machine learning algorithm to provide powerful user authentication[5]. The system uses a cryptographic layer to enhance the data security by encrypting user-related information with sensitive files using the Advanced encryption Standard (AES) encryption[4]. The authentication and encryption tasks are performed in order to ensure identity verification and safe data protection[6]. The system is tested using publicly available EEG datasets, thus showing that it is possible to perform EEG-based authentication under a controlled setting[7]. The results show that a neural signal analysis, machine learning, and cryptographic method have been combined to produce a strong and multi-layered security system[8]. The paper preconditions the future real-time applications, which could utilize wearable EEG sensors and IoT-based systems with the goal of improving the usability and supporting the working implementation of the application in secure access-control settings[9].

Abirami S, Dr.K.Banuroopa,"Brainwave-Based Secure Authentication Using Neural Identity Patterns" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(1): Page(1389-1394) Jan-Feb 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.