Biblio

This document paper presents a critical and condensed analyze on series of devices that are intended for the military field, making an overview analysis of the technical solutions presented and that identifying those aspects that are really important for the military field or that offering a new approach. We currently have a wide range of medical devices that can be adapted for use in the military, but this adaptation must follow some well-defined aspects. A device that does not offer 100% reliability will be difficult to adopt in a military system, where mistakes are not allowed.

This manuscript prescribes the design of a four-port ultra-wideband (UWB) diversity antenna combined with 2.4 GHz ISM radio band. The denim-based wearable antenna is intended for use as a radio frequency identification (RFID) tag for tracking and security applications. The unit cells of the antenna are arranged orthogonally to each other to achieve isolation \$\textbackslashtextbackslashgt15\$ dB. The bending analysis of the proposed antenna is performed to ensure its stability. The dimensions of the unit cell and four-port MIMO antenna are \$30 \textbackslashtextbackslashtimes 17 \textbackslashtextbackslashtimes 1\$ cubic millimeter and \$55 \textbackslashtextbackslashtimes 53 \textbackslashtextbackslashtimes 1\$ cubic millimeter, respectively. The proposed antenna’s specific absorption rate (SAR) is researched in order to determine the safer SAR limit set by the Federal Communications Commission (FCC).

Future wearable devices are expected to increasingly exchange their positioning information with various Location-Based Services (LBSs). Wearable applications can include activity-based health and fitness recommendations, location-based social networking, location-based gamification, among many others. With the growing opportunities for LBSs, it is expected that location privacy concerns will also increase significantly. Particularly, in opportunistic wireless networks based on device-to-device (D2D) connectivity, a user can request a higher level of control over own location privacy, which may result in more flexible permissions granted to wearable devices. This translates into the ability to perform location obfuscation to the desired degree when interacting with other wearables or service providers across the network. In this paper, we argue that specific errors in the disclosed location information feature two components: a measurement error inherent to the localization algorithm used by a wearable device and an intentional (or obfuscation) error that may be based on a trade-off between a particular LBS and a desired location privacy level. This work aims to study the trade-off between positioning accuracy and location information privacy in densely crowded scenarios by introducing two privacy-centric metrics.

Bluetooth enables excellent mobility in Brain Computer Interface (BCI) research and other use cases including ambulatory care, telemedicine, fitness tracking and mindfulness training. Although significant research exists for an all-encompassing BCI performance rating, almost all the literature addresses performance in terms of brain state or brain function classification accuracy. For the few published experiments that address BCI hardware performance, they too, focused on improving classification accuracy. This paper explores some of the more recent studies and proposes a trusted performance rating for BCI applications based on the enhanced privacy, yet reduced bandwidth needs of mobile EEG-based BCI applications. This paper proposes a set of Bluetooth operating parameters required to meet the performance, usability and privacy requirements of reliable and secure mobile neuro-feedback applications. It presents a rating model, "Trusted Mobile BCI", based on those operating parameters, and validated the model with studies that leveraged mobile BCI technology.

Wearable devices, such as smartwatches, are furnished with state-of-the-art sensors that enable a range of context-aware applications. However, malicious applications can misuse these sensors, if access is left unaudited. In this paper, we demonstrate how applications that have access to motion or inertial sensor data on a modern smartwatch can recover text typed on an external QWERTY keyboard. Due to the distinct nature of the perceptible motion sensor data, earlier research efforts on emanation based keystroke inference attacks are not readily applicable in this scenario. The proposed novel attack framework characterizes wrist movements (captured by the inertial sensors of the smartwatch worn on the wrist) observed during typing, based on the relative physical position of keys and the direction of transition between pairs of keys. Eavesdropped keystroke characteristics are then matched to candidate words in a dictionary. Multiple evaluations show that our keystroke inference framework has an alarmingly high classification accuracy and word recovery rate. With the information recovered from the wrist movements perceptible by a smartwatch, we exemplify the risks associated with unaudited access to seemingly innocuous sensors (e.g., accelerometers and gyroscopes) of wearable devices. As part of our efforts towards preventing such side-channel attacks, we also develop and evaluate a novel context-aware protection framework which can be used to automatically disable (or downgrade) access to motion sensors, whenever typing activity is detected.

Securely pairing wearables with another device is the key to many promising applications, such as mobile payment, sensitive data transfer and secure interactions with smart home devices. This paper presents Touch-And-Guard (TAG), a system that uses hand touch as an intuitive manner to establish a secure connection between a wristband wearable and the touched device. It generates secret bits from hand resonant properties, which are obtained using accelerometers and vibration motors. The extracted secret bits are used by both sides to authenticate each other and then communicate confidentially. The ubiquity of accelerometers and motors presents an immediate market for our system. We demonstrate the feasibility of our system using an experimental prototype and conduct experiments involving 12 participants with 1440 trials. The results indicate that we can generate secret bits at a rate of 7.84 bit/s, which is 58% faster than conventional text input PIN authentication. We also show that our system is resistant to acoustic eavesdroppers in proximity.