Anindya Maiti, Murtuza Jadliwala, Jibo He, Igor Bilogrevic
{"title":"(Smart)watch your taps: side-channel keystroke inference attacks using smartwatches","authors":"Anindya Maiti, Murtuza Jadliwala, Jibo He, Igor Bilogrevic","doi":"10.1145/2802083.2808397","DOIUrl":"https://doi.org/10.1145/2802083.2808397","url":null,"abstract":"In this paper, we investigate the feasibility of keystroke inference attacks on handheld numeric touchpads by using smartwatch motion sensors as a side-channel. The proposed attack approach employs supervised learning techniques to accurately map the uniqueness in the captured wrist movements to each individual keystroke. Experimental evaluation shows that keystroke inference using smartwatch motion sensors is not only fairly accurate, but also better than similar attacks previously demonstrated using smartphone motion sensors.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116611970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"PneuHaptic: delivering haptic cues with a pneumatic armband","authors":"Liang He, Cheng Xu, Ding Xu, Ryan Brill","doi":"10.1145/2802083.2802091","DOIUrl":"https://doi.org/10.1145/2802083.2802091","url":null,"abstract":"PneuHaptic is a pneumatically-actuated arm-worn haptic interface. The system triggers a range of tactile sensations on the arm by alternately pressurizing and depressurizing a series of custom molded silicone chambers. We detail the implementation of our functional prototype and explore the possibilities for interaction enabled by the system.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132028230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Song, Geeyoung Noh, Junwoo Yoo, Ian Oakley, Jun-Dong Cho, Andrea Bianchi
{"title":"Hot & tight: exploring thermo and squeeze cues recognition on wrist wearables","authors":"S. Song, Geeyoung Noh, Junwoo Yoo, Ian Oakley, Jun-Dong Cho, Andrea Bianchi","doi":"10.1145/2802083.2802092","DOIUrl":"https://doi.org/10.1145/2802083.2802092","url":null,"abstract":"Wrist worn wearable computing devices are ideally suited for presenting notifications through haptic stimuli as they are always in direct contact with the user's skin. While prior work has explored the feasibility of haptic notifications, we highlight a lack of empirical studies on thermal and pressure feedback in the context of wearable devices. This paper introduces prototypes for thermal and pressure (squeeze) feedback on the wrist. It then presents a study characterizing recognition performance with thermal and pressure cues against baseline performance with vibrations.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124797657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recognizing new activities with limited training data","authors":"Le T. Nguyen, Mingzhi Zeng, P. Tague, J. Zhang","doi":"10.1145/2802083.2808388","DOIUrl":"https://doi.org/10.1145/2802083.2808388","url":null,"abstract":"Activity recognition (AR) systems are typically built to recognize a predefined set of common activities. However, these systems need to be able to learn new activities to adapt to a user's needs. Learning new activities is especially challenging in practical scenarios when a user provides only a few annotations for training an AR model. In this work, we study the problem of recognizing new activities with a limited amount of labeled training data. Due to the shortage of labeled data, small variations of the new activity will not be detected resulting in a significant degradation of the system's recall. We propose the FE-AT (Feature-based and Attribute-based learning) approach, which leverages the relationship between existing and new activities to compensate for the shortage of the labeled data. We evaluate FE-AT on three public datasets and demonstrate that it outperforms traditional AR approaches in recognizing new activities, especially when only a few training instances are available.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126460345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cynthia E. Rogers, Alexander W. Witt, Alexander D. Solomon, K. Venkatasubramanian
{"title":"An approach for user identification for head-mounted displays","authors":"Cynthia E. Rogers, Alexander W. Witt, Alexander D. Solomon, K. Venkatasubramanian","doi":"10.1145/2802083.2808391","DOIUrl":"https://doi.org/10.1145/2802083.2808391","url":null,"abstract":"A head-mounted display (HMD) is a device, worn by a person, which has a display in front of one or both eyes. HMDs have applications in a variety of domains including gaming, virtual reality, and medicine. In this paper we present an approach that can identify a user, from among a group of users, by synchronously capturing their unconscious blinking and head-movements using integrated HMD sensors. We ask each user of the HMD to view a series of rapidly changing images of numbers and letters on the HMD display. Simultaneously, their blinks and head-movements are captured using infrared, accelerometer, and gyroscope sensors. Analysis of our approach using blink and head-movement data collected from 20 individuals demonstrates the feasibility of our approach with an accuracy of ~94%.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122542320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Controlling stiffness with jamming for wearable haptics","authors":"Tim Simon, B. Thomas, Ross T. Smith","doi":"10.1145/2802083.2808401","DOIUrl":"https://doi.org/10.1145/2802083.2808401","url":null,"abstract":"Layer jamming devices enhance wearable technologies by providing haptic feedback through stiffness control. In this paper we present our prototype that demonstrates improved haptic fidelity of a wearable layer jamming device, using computer controlled solenoid to enable fine-grained control of the garments stiffness property. We also explore variable stiffness configurations for virtual UI components. An evaluation was conducted to validate the methodology, demonstrating dynamic stiffness control with a two waveforms.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126848804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"WISEglass: multi-purpose context-aware smart eyeglasses","authors":"Florian Wahl, Martin Freund, O. Amft","doi":"10.1145/2802083.2808409","DOIUrl":"https://doi.org/10.1145/2802083.2808409","url":null,"abstract":"We extend regular eyeglasses with multi-modal sensing and processing functions for context awareness. Our aim was to leverage eyeglasses as a platform to acquire and process context information according to the wearer's needs. The eyeglasses provide inertial motion, environmental light, and pulse sensors, data processing and wireless functionality, besides a rechargeable battery. We implemented prototypes of the smart eyeglasses and evaluated recognition performance in a study of daily activities with nine participants. The accuracy of recognising nine activity clusters from the smart eyeglasses motion sensors was 77% on average, confirming the benefit of smart eyeglasses for context-aware applications.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114454236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"New directions in jewelry: a close look at emerging trends & developments in jewelry-like wearable devices","authors":"Yulia Silina, H. Haddadi","doi":"10.1145/2802083.2808410","DOIUrl":"https://doi.org/10.1145/2802083.2808410","url":null,"abstract":"As wearables are entering the domain of fashion, it is not uncommon to see criticisms of their unfashionable aesthetics and gadgetry that do not necessarily consider consumer preferences and a need to create desire for wearable objects. As other categories of wearable devices, jewelry-like devices are in the process of undergoing a profound and rapid change. In this paper, we examine 187 jewelry-like devices that are either already available on the market, or are at various stages of development and research. We then examine various parameters using descriptive statistics, and give an overview of some major emerging trends and developments in jewelry-like devices. We then highlight and propose directions for technical features, use of material and interacting modalities and so on that could be applied in the development of the future computational jewelry devices.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115669659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Tracking motion context of railway passengers by fusion of low-power sensors in mobile devices","authors":"Takamasa Higuchi, H. Yamaguchi, T. Higashino","doi":"10.1145/2802083.2808387","DOIUrl":"https://doi.org/10.1145/2802083.2808387","url":null,"abstract":"In this paper we develop StationSense, a novel mobile sensing solution for precisely tracking temporal stop-and-go patterns of railway passengers. While such motion context serves as a promising enabler of various traveler support systems, we found through experiments in a major railway network in Japan that existing accelerometer-based passenger tracking systems can poorly work in modern trains, where jolts during motion have been dramatically reduced. Towards robust motion tracking, StationSense harnesses characteristic features in ambient magnetic fields in trains to find candidates of stationary periods, and subsequently filters out false positive detections by a tailored acceleration fusion mechanism. Then it finds optimal boundaries between adjacent moving/stationary periods, employing unique signatures in accelerometer readings. Through field experiments around 16 railway lines, we show that StationSense can identify periods of train stops with accuracy of 81%, which is almost 2 times higher than the existing accelerometer-based solutions.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121908359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A wearable system for detecting eating activities with proximity sensors in the outer ear","authors":"Abdelkareem Bedri, Apoorva Verlekar, Edison Thomaz, Valerie Avva, Thad Starner","doi":"10.1145/2802083.2808411","DOIUrl":"https://doi.org/10.1145/2802083.2808411","url":null,"abstract":"This paper presents an approach for automatically detecting eating activities by measuring deformations in the ear canal walls due to mastication activity. These deformations are measured with three infrared proximity sensors encapsulated in an off-the-shelf earpiece. To evaluate our method, we conducted a user study in a lab setting where 20 participants were asked to perform eating and non-eating activities. A user dependent analysis demonstrated that eating could be detected with 95.3% accuracy. This result indicates that proximity sensing offers an alternative to acoustic and inertial sensing in eating detection while providing benefits in terms of privacy and robustness to noise.","PeriodicalId":372395,"journal":{"name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125115114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}