Using vibrations from a SmartRing as an out-of-band channel for sharing secret keys

With the rapid growth in the number of Internet of Things (IoT) devices with wireless communication capabilities, and sensitive information collection capabilities, it is becoming increasingly necessary to ensure that these devices communicate securely with only authorized devices. A major requirement of this secure communication is to ensure that both the devices share a secret, which can be used for secure pairing and encrypted communication. Manually imparting this secret to these devices becomes an unnecessary overhead, especially when the device interaction is transient. In this work, we empirically investigate the possibility of using an out-of-band communication channel – vibration, generated by a custom smartRing – to share a secret with a compatible IoT device. Through a user study with 12 participants we show that in the best case we can exchange 85.9% messages successfully. Our technique demonstrates the possibility of sharing messages accurately, quickly and securely as compared to several existing techniques

MobiSys 2016

The 14th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2016) spanned a range of themes and domains, from smart environments to security and privacy. The highlights presented here cover the keynotes, paper sessions, and first Asian Students Symposium on Emerging Technologies

Design of Delta Sigma Modulators for Integrated Sensor Applications

The paper presents and explores the implementation of Delta Sigma Modulators for Integrated sensor applications. Elaborate design procedures and trade-offs faced have been presented. Starting at the block and topology level, comparisons of various feasible choices have been presented, along with the suited applications. Circuit level comparisons and trade-offs such as OTA and comparator design have also been presented. Finally, simulations have been shown for a modulator designed as per above criteria for integrated accelerometer applications. Keywords: MEMS, Delta Sigma Modulators, Dynamic Range, Integrated sensor

The Case for Smartwatch-based Diet Monitoring

Ministry of Education, Singapore under its Academic Research Funding Tier

Inferring smartphone keypress via smartwatch inertial sensing

Ministry of Education, Singapore under its Academic Research Funding Tier

Evaluating the Reproducibility of Physiological Stress Detection Models

Recent advances in wearable sensor technologies have led to a variety of approaches for detecting physiological stress. Even with over a decade of research in the domain, there still exist many significant challenges, including a near-total lack of reproducibility across studies. Researchers often use some physiological sensors (custom-made or off-the-shelf), conduct a study to collect data, and build machine-learning models to detect stress. There is little effort to test the applicability of the model with similar physiological data collected from different devices, or the efficacy of the model on data collected from different studies, populations, or demographics. This paper takes the first step towards testing reproducibility and validity of methods and machine-learning models for stress detection. To this end, we analyzed data from 90 participants, from four independent controlled studies, using two different types of sensors, with different study protocols and research goals. We started by evaluating the performance of models built using data from one study and tested on data from other studies. Next, we evaluated new methods to improve the performance of stress-detection models and found that our methods led to a consistent increase in performance across all studies, irrespective of the device type, sensor type, or the type of stressor. Finally, we developed and evaluated a clustering approach to determine the stressed/not-stressed classification when applying models on data from different studies, and found that our approach performed better than selecting a threshold based on training data. This paper\u27s thorough exploration of reproducibility in a controlled environment provides a critical foundation for deeper study of such methods, and is a prerequisite for tackling reproducibility in free-living conditions

Did you take a break today? Detecting playing foosball using your smartwatch

Ministry of Education, Singapore under its Academic Research Funding Tier 2; National Research Foundation (NRF) Singapore under IDM Futures Funding Initiativ

The Case for Cloud-Enabled Mobile Sensing Services

Singapore MOE Academic Research Fund Tier