With the advent of wearable devices and commonality of on-body monitoring devices, it is anticipated that a day will come in the future where body-area networks will become commonplace in our lives. It is envisioned that the whole process will be automated wherein a user wearing such a device automatically enables the security mechanism and establishes communication between that user and his/her surroundings. This paper addresses a technique to identify the wearer of the device by way of Gaussian Mixture Models (GMM), allowing for identification and verification before establishing communication. It suggests using gait as a metric for identity association using wearable sensors.
Wearable technology is rapidly changing the way we associate objects with our surroundings, and how we interact with the objects. As technology becomes more commonplace in our surroundings, our lives are rendered more vulnerable. As technology becomes more sophisticated, our interaction with it seems to become progressively minimalistic. This chapter introduces techniques wherein secure communication between humans and their surrounding devices can be facilitated by applying human physiological information as the identifying factor. Different biometric techniques are investigated, and the rationale behind their applicability is argued. Additionally, the benefits and possible use-cases for each technique is presented, and the associated open research problems are brought to light.
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