Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services最新文献_第4页

FOCUS: Robust Visual Codes for Everyone 重点:适合所有人的健壮的视觉代码

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906399

Frederik Hermans, L. McNamara, Gábor Sörös, C. Rohner, T. Voigt, E. Ngai

引用次数: 16

Platypus: Indoor Localization and Identification through Sensing of Electric Potential Changes in Human Bodies 鸭嘴兽:通过人体电位变化感知的室内定位和识别

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906402

T. Große-Puppendahl, Xavier Dellangnol, C. Hatzfeld, Biying Fu, M. Kupnik, Arjan Kuijper, Matthias R. Hastall, James Scott, M. Gruteser

{"title":"Platypus: Indoor Localization and Identification through Sensing of Electric Potential Changes in Human Bodies","authors":"T. Große-Puppendahl, Xavier Dellangnol, C. Hatzfeld, Biying Fu, M. Kupnik, Arjan Kuijper, Matthias R. Hastall, James Scott, M. Gruteser","doi":"10.1145/2906388.2906402","DOIUrl":"https://doi.org/10.1145/2906388.2906402","url":null,"abstract":"Platypus is the first system to localize and identify people by remotely and passively sensing changes in their body electric potential which occur naturally during walking. While it uses three or more electric potential sensors with a maximum range of 2 m, as a tag-free system it does not require the user to carry any special hardware. We describe the physical principles behind body electric potential changes, and a predictive mathematical model of how this affects a passive electric field sensor. By inverting this model and combining data from sensors, we infer a method for localizing people and experimentally demonstrate a median localization error of 0.16 m. We also use the model to remotely infer the change in body electric potential with a mean error of 8.8 % compared to direct contact-based measurements. We show how the reconstructed body electric potential differs from person to person and thereby how to perform identification. Based on short walking sequences of 5 s, we identify four users with an accuracy of 94 %, and 30 users with an accuracy of 75 %. We demonstrate that identification features are valid over multiple days, though change with footwear.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127606944","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}

引用次数: 64

Session details: Session IV: Transit and Mapping 会议详情:第四部分:运输和映射

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/3257199

R. Kravets

引用次数: 0

Practical Bluetooth Traffic Sniffing: Systems and Privacy Implications 实用蓝牙流量嗅探:系统和隐私含义

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906403

Wahhab Albazrqaoe, Jun Huang, G. Xing

{"title":"Practical Bluetooth Traffic Sniffing: Systems and Privacy Implications","authors":"Wahhab Albazrqaoe, Jun Huang, G. Xing","doi":"10.1145/2906388.2906403","DOIUrl":"https://doi.org/10.1145/2906388.2906403","url":null,"abstract":"With the prevalence of personal Bluetooth devices, potential breach of user privacy has been an increasing concern. To date, sniffing Bluetooth traffic has been widely considered an extremely intricate task due to Bluetooth's indiscoverable mode, vendor-dependent adaptive hopping behavior, and the interference in the open 2.4 GHz band. In this paper, we present BlueEar -a practical Bluetooth traffic sniffer. BlueEar features a novel dual-radio architecture where two Bluetooth-compliant radios coordinate with each other on learning the hopping sequence of indiscoverable Bluetooth networks, predicting adaptive hopping behavior, and mitigating the impacts of RF interference. Experiment results show that BlueEar can maintain a packet capture rate higher than 90% consistently in real-world environments, where the target Bluetooth network exhibits diverse hopping behaviors in the presence of dynamic interference from coexisting Wi-Fi devices. In addition, we discuss the privacy implications of the BlueEar system, and present a practical countermeasure that effectively reduces the packet capture rate of the sniffer to 20%. The proposed countermeasure can be easily implemented on the Bluetooth master device while requiring no modification to slave devices like keyboards and headsets.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126446948","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}

引用次数: 44

Practical Human Sensing in the Light 光中的实用人类感知

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906401

Tianxing Li, Qiang Liu, Xia Zhou

{"title":"Practical Human Sensing in the Light","authors":"Tianxing Li, Qiang Liu, Xia Zhou","doi":"10.1145/2906388.2906401","DOIUrl":"https://doi.org/10.1145/2906388.2906401","url":null,"abstract":"We present StarLight, an infrastructure-based sensing system that reuses light emitted from ceiling LED panels to reconstruct fine-grained user skeleton postures continuously in real time. It relies on only a few (e.g., 20) photodiodes placed at optimized locations to passively capture low-level visual clues (light blockage information), with neither cameras capturing sensitive images, nor on-body devices, nor electromagnetic interference. It then aggregates the blockage information of a large number of light rays from LED panels and identifies best-fit 3D skeleton postures. StarLight greatly advances the prior light-based sensing design by dramatically reducing the number of intrusive sensors, overcoming furniture blockage, and supporting user mobility. We build and deploy StarLight in a 3.6 m x 4.8 m office room, with customized 20 LED panels and 20 photodiodes. Experiments show that StarLight achieves 13.6 degree mean angular error for five body joints and reconstructs a mobile skeleton at a high frame rate (40 FPS). StarLight enables a new unobtrusive sensing paradigm to augment today's mobile sensing for continuous and accurate behavioral monitoring.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129616941","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}

引用次数: 119

TransitLabel: A Crowd-Sensing System for Automatic Labeling of Transit Stations Semantics TransitLabel:公交站点语义自动标注的人群感知系统

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-10 DOI: 10.1145/2906388.2906395

Moustafa Elhamshary, M. Youssef, A. Uchiyama, H. Yamaguchi, T. Higashino

{"title":"TransitLabel: A Crowd-Sensing System for Automatic Labeling of Transit Stations Semantics","authors":"Moustafa Elhamshary, M. Youssef, A. Uchiyama, H. Yamaguchi, T. Higashino","doi":"10.1145/2906388.2906395","DOIUrl":"https://doi.org/10.1145/2906388.2906395","url":null,"abstract":"We present TransitLabel, a crowd-sensing system for automatic enrichment of transit stations indoor floorplans with different semantics like ticket vending machines, entrance gates, drink vending machines, platforms, cars' waiting lines, restrooms, lockers, waiting (sitting) areas, among others. Our key observations show that certain passengers' activities (e.g., purchasing tickets, crossing entrance gates, etc) present identifiable signatures on one or more cell-phone sensors. TransitLabel leverages this fact to automatically and unobtrusively recognize different passengers' activities, which in turn are mined to infer their uniquely associated stations semantics. Furthermore, the locations of the discovered semantics are automatically estimated from the inaccurate passengers' positions when these semantics are identified. We evaluate TransitLabel through a field experiment in eight different train stations in Japan. Our results show that TransitLabel can detect the fine-grained stations semantics accurately with 7.7% false positive rate and 7.5% false negative rate on average. In addition, it can consistently detect the location of discovered semantics accurately, achieving an error within 2.5m on average for all semantics. Finally, we show that TransitLabel has a small energy footprint on cell-phones, could be generalized to other stations, and is robust to different phone placements; highlighting its promise as a ubiquitous indoor maps enriching service.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124905184","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}

引用次数: 86

ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic ReCon:揭示和控制移动网络流量中的PII泄漏

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2015-07-01 DOI: 10.1145/2906388.2906392

Jingjing Ren, Ashwin Rao, Martina Lindorfer, A. Legout, D. Choffnes

{"title":"ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic","authors":"Jingjing Ren, Ashwin Rao, Martina Lindorfer, A. Legout, D. Choffnes","doi":"10.1145/2906388.2906392","DOIUrl":"https://doi.org/10.1145/2906388.2906392","url":null,"abstract":"It is well known that apps running on mobile devices extensively track and leak users' personally identifiable information (PII); however, these users have little visibility into PII leaked through the network traffic generated by their devices, and have poor control over how, when and where that traffic is sent and handled by third parties. In this paper, we present the design, implementation, and evaluation of ReCon: a cross-platform system that reveals PII leaks and gives users control over them without requiring any special privileges or custom OSes. ReCon leverages machine learning to reveal potential PII leaks by inspecting network traffic, and provides a visualization tool to empower users with the ability to control these leaks via blocking or substitution of PII. We evaluate ReCon's effectiveness with measurements from controlled experiments using leaks from the 100 most popular iOS, Android, and Windows Phone apps, and via an IRB-approved user study with 92 participants. We show that ReCon is accurate, efficient, and identifies a wider range of PII than previous approaches.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123810338","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}

引用次数: 212