Abstract
The Internet-of-Things (IoT) is an emerging paradigm seamlessly integrating a great number of smart objects ubiquitously connected to the Internet. With the rise in interest in the IoT, industry and academia have introduced a variety of authentication technologies to deal with security challenges. Authentication in IoT involves not only shifting intelligent access control down to the end smart objects, but also user identification and verification. In this paper, we build an authentication system based on brainwave reactions to a chain of events. Brainwaves, as external signals of a functioning brain, provide a glimpse into how we think and react. However, seen another way, we could reasonably expect that a given action or event could be linked back to its corresponding brainwave reaction. Recently, commercial products in the form of wearable brainwave headsets have appeared on the market, opening up the possibility of exploiting brainwaves for various purposes and making this more feasible. In the proposed system, we use a commercially available brainwave headset to collect brainwave data from participants for use in the proposed authentication system. After the brainwave data collection process, we apply a machine learning-based approach to extract features from brainwaves to serve as authentication tokens in the system and support the authentication system itself.
Highlights
IoT stands for the Internet of Things, a concept that has become one of the most oft-mentioned topics in the computer domain
We focus on the biometric-based continuous authentication model
Crawford pointed out that transparent authentication has the following benefits over traditional methods [16]: Effortless: Since the behavioral biometrics are gathered in the background, during regular device use, the user does not need to interrupt his/her tasks to authenticate
Summary
IoT stands for the Internet of Things, a concept that has become one of the most oft-mentioned topics in the computer domain. The prospect of an IoT-based economic system has brought small, embeddable devices with Internet connectivity and data collection capabilities to the market and they are becoming increasingly commonplace in our daily life. These devices are mostly resource-limited and, in many cases, implemented with microcontrollers and equipped with little usable memory [1]. Most IoT devices lack a fully functional user interaction interface, which makes the implementation of traditional authentication schemes in the IoT impractical. More wearable brainwave-sensing devices have entered the market, lowering the barriers to collecting brainwave data and performing research on brainwaves As this trend continues, further such usage of brainwave data can be anticipated.
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