2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)最新文献

Combined heat and privacy: Preventing occupancy detection from smart meters 热和隐私的结合:防止智能电表的占用检测

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813962

Dong Chen, David E. Irwin, P. Shenoy, Jeannie R. Albrecht

{"title":"Combined heat and privacy: Preventing occupancy detection from smart meters","authors":"Dong Chen, David E. Irwin, P. Shenoy, Jeannie R. Albrecht","doi":"10.1109/PerCom.2014.6813962","DOIUrl":"https://doi.org/10.1109/PerCom.2014.6813962","url":null,"abstract":"Electric utilities are rapidly deploying smart meters that record and transmit electricity usage in real-time. As prior research shows, smart meter data indirectly leaks sensitive, and potentially valuable, information about a home's activities. An important example of the sensitive information smart meters reveal is occupancy-whether or not someone is home and when. As prior work also shows, occupancy is surprisingly easy to detect, since it highly correlates with simple statistical metrics, such as power's mean, variance, and range. Unfortunately, prior research that uses chemical energy storage, e.g., batteries, to prevent appliance power signature detection is prohibitively expensive when applied to occupancy detection. To address this problem, we propose preventing occupancy detection using the thermal energy storage of large elastic heating loads already present in many homes, such as electric water and space heaters. In essence, our approach, which we call Combined Heat and Privacy (CHPr), controls the power usage of these large loads to make it look like someone is always home. We design a CHPr-enabled water heater that regulates its energy usage to mask occupancy without violating its objective, e.g., to provide hot water on demand, and evaluate it in simulation and using a prototype. Our results show that a 50-gallon CHPr-enabled water heater decreases the Matthews Correlation Coefficient (a standard measure of a binary classifier's performance) of a threshold-based occupancy detection attack in a representative home by 10x (from 0.44 to 0.045), effectively preventing occupancy detection at no extra cost.","PeriodicalId":263520,"journal":{"name":"2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122947377","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: 38

Capacity of pervasive camera based communication under perspective distortions 视角畸变下基于普适相机的通信能力

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813951

A. Ashok, Shubham Jain, M. Gruteser, N. Mandayam, Wenjia Yuan, Kristin J. Dana

{"title":"Capacity of pervasive camera based communication under perspective distortions","authors":"A. Ashok, Shubham Jain, M. Gruteser, N. Mandayam, Wenjia Yuan, Kristin J. Dana","doi":"10.1109/PerCom.2014.6813951","DOIUrl":"https://doi.org/10.1109/PerCom.2014.6813951","url":null,"abstract":"Cameras are ubiquitous and increasingly being used not just for capturing images but also for communicating information. For example, the pervasive QR codes can be viewed as communicating a short code to camera-equipped sensors and recent research has explored using screen-to-camera communications for larger data transfers. Such communications could be particularly attractive in pervasive camera based applications, where such camera communications can reuse the existing camera hardware and also leverage from the large pixel array structure for high data-rate communication. While several prototypes have been constructed, the fundamental capacity limits of this novel communication channel in all but the simplest scenarios remains unknown. The visual medium differs from RF in that the information capacity of this channel largely depends on the perspective distortions while multipath becomes negligible. In this paper, we create a model of this communication system to allow predicting the capacity based on receiver perspective (distance and angle to the transmitter). We calibrate and validate this model through lab experiments wherein information is transmitted from a screen and received with a tablet camera. Our capacity estimates indicate that tens of Mbps is possible using a smartphone camera even when the short code on the screen images onto only 15% of the camera frame. Our estimates also indicate that there is room for at least 2.5x improvement in throughput of existing screen - camera communication prototypes.","PeriodicalId":263520,"journal":{"name":"2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131209035","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: 41

Comparing and fusing different sensor modalities for relay attack resistance in Zero-Interaction Authentication 零交互认证中不同传感器抗中继攻击的比较与融合

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813957

H. Truong, Xiang Gao, B. Shrestha, Nitesh Saxena, N. Asokan, P. Nurmi

{"title":"Comparing and fusing different sensor modalities for relay attack resistance in Zero-Interaction Authentication","authors":"H. Truong, Xiang Gao, B. Shrestha, Nitesh Saxena, N. Asokan, P. Nurmi","doi":"10.1109/PerCom.2014.6813957","DOIUrl":"https://doi.org/10.1109/PerCom.2014.6813957","url":null,"abstract":"Zero-Interaction Authentication (ZIA) refers to approaches that authenticate a user to a verifier (terminal) without any user interaction. Currently deployed ZIA solutions are predominantly based on the terminal detecting the proximity of the user's personal device, or a security token, by running an authentication protocol over a short-range wireless communication channel. Unfortunately, this simple approach is highly vulnerable to low-cost and practical relay attacks which completely offset the usability benefits of ZIA. The use of contextual information, gathered via on-board sensors, to detect the co-presence of the user and the verifier is a recently proposed mechanism to resist relay attacks. In this paper, we systematically investigate the performance of different sensor modalities for co-presence detection with respect to a standard Dolev-Yao adversary. First, using a common data collection framework run in realistic everyday settings, we compare the performance of four commonly available sensor modalities (WiFi, Bluetooth, GPS, and Audio) in resisting ZIA relay attacks, and find that WiFi is better than the rest. Second, we show that, compared to any single modality, fusing multiple modalities improves resilience against ZIA relay attacks while retaining a high level of usability. Third, we motivate the need for a stronger adversarial model to characterize an attacker who can compromise the integrity of context sensing itself. We show that in the presence of such a powerful attacker, each individual sensor modality offers very low security. Positively, the use of multiple sensor modalities improves security against such an attacker if the attacker cannot compromise multiple modalities simultaneously.","PeriodicalId":263520,"journal":{"name":"2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133960512","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: 74

Analysis methods for extracting knowledge from large-scale WiFi monitoring to inform building facility planning 从大规模WiFi监控中提取知识，为建筑设施规划提供信息的分析方法

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813953

A. R. Ruiz, H. Blunck, Thor S. Prentow, Allan Stisen, M. Kjærgaard

{"title":"Analysis methods for extracting knowledge from large-scale WiFi monitoring to inform building facility planning","authors":"A. R. Ruiz, H. Blunck, Thor S. Prentow, Allan Stisen, M. Kjærgaard","doi":"10.1109/PerCom.2014.6813953","DOIUrl":"https://doi.org/10.1109/PerCom.2014.6813953","url":null,"abstract":"The optimization of logistics in large building complexes with many resources, such as hospitals, require realistic facility management and planning. Current planning practices rely foremost on manual observations or coarse unverified assumptions and therefore do not properly scale or provide realistic data to inform facility planning. In this paper, we propose analysis methods to extract knowledge from large sets of network collected WiFi traces to better inform facility management and planning in large building complexes. The analysis methods, which build on a rich set of temporal and spatial features, include methods for noise removal, e.g., labeling of beyond building-perimeter devices, and methods for quantification of area densities and flows, e.g., building enter and exit events, and for classifying the behavior of people, e.g., into user roles such as visitor, hospitalized or employee. Spatio-temporal visualization tools built on top of these methods enable planners to inspect and explore extracted information to inform facility-planning activities. To evaluate the methods, we present results for a large hospital complex covering more than 10 hectares. The evaluation is based on WiFi traces collected in the hospital's WiFi infrastructure over two weeks observing around 18000 different devices recording more than a billion individual WiFi measurements. For the presented analysis methods we present quantitative performance results, e.g., demonstrating over 95% accuracy for correct noise removal of beyond building perimeter devices. We furthermore present detailed statistics from our analysis regarding people's presence, movement and roles, and example types of visualizations that both highlight their potential as inspection tools for planners and provide interesting insights into the test-bed hospital.","PeriodicalId":263520,"journal":{"name":"2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133514864","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: 105

Unleashing the Wild Card for mobile payment 释放移动支付的不确定因素

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813952

M. Salajegheh, B. Priyantha, Jie Liu

引用次数: 3

Multi-scale Conditional Random Fields for first-person activity recognition 第一人称活动识别的多尺度条件随机场

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813944

Kai Zhan, S. Faux, F. Ramos

{"title":"Multi-scale Conditional Random Fields for first-person activity recognition","authors":"Kai Zhan, S. Faux, F. Ramos","doi":"10.1109/PerCom.2014.6813944","DOIUrl":"https://doi.org/10.1109/PerCom.2014.6813944","url":null,"abstract":"We propose a novel pervasive system to recognise human daily activities from a wearable device. The system is designed in a form of reading glasses, named `Smart Glasses', integrating a 3-axis accelerometer and a first-person view camera. Our aim is to classify user's activities of daily living (ADLs) based on both vision and head motion data. This ego-activity recognition system not only allows caretakers to track on a specific person (such as patient or elderly people), but also has the potential to remind/warn people with cognitive impairments of hazardous situations. We present the following contributions in this paper: a feature extraction method from accelerometer and video; a classification algorithm integrating both locomotive (body motions) and stationary activities (without or with small motions); a novel multi-scale dynamic graphical model structure for structured classification over time. We collect, train and validate our system on a large dataset containing 20 hours of ADLs data, including 12 daily activities under different environmental settings. Our method improves the classification performance (F-Score) of conventional approaches from 43.32%(video features) and 66.02%(acceleration features) by an average of 20-40% to 84.45%, with an overall accuracy of 90.04% in realistic ADLs.","PeriodicalId":263520,"journal":{"name":"2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124508692","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: 91

From proximity sensing to spatio-temporal social graphs 从接近感测到时空社会图谱

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813947

Claudio Martella, M. Dobson, A. V. Halteren, M. Steen

引用次数: 20

Incremental Wi-Fi scanning for energy-efficient localization 增量Wi-Fi扫描，实现节能定位

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813956

N. Brouwers, Marco Zúñiga, K. Langendoen

引用次数: 42

MapGENIE: Grammar-enhanced indoor map construction from crowd-sourced data MapGENIE:基于众包数据的语法增强的室内地图构建

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813954

D. Philipp, P. Baier, Christoph Dibak, Frank Dürr, K. Rothermel, S. Becker, M. Peter, D. Fritsch

{"title":"MapGENIE: Grammar-enhanced indoor map construction from crowd-sourced data","authors":"D. Philipp, P. Baier, Christoph Dibak, Frank Dürr, K. Rothermel, S. Becker, M. Peter, D. Fritsch","doi":"10.1109/PerCom.2014.6813954","DOIUrl":"https://doi.org/10.1109/PerCom.2014.6813954","url":null,"abstract":"While location-based services are already well established in outdoor scenarios, they are still not available in indoor environments. The reason for this can be found in two open problems: First, there is still no off-the-shelf indoor positioning system for mobile devices and, second, indoor maps are not publicly available for most buildings. While there is an extensive body of work on the first problem, the efficient creation of indoor maps remains an open challenge. We tackle the indoor mapping challenge in our MapGENIE approach that automatically derives indoor maps from traces collected by pedestrians moving around in a building. Since the trace data is collected in the background from the pedestrians' mobile devices, MapGENIE avoids the labor-intensive task of traditional indoor map creation and increases the efficiency of indoor mapping. To enhance the map building process, MapGENIE leverages exterior information about the building and uses grammars to encode structural information about the building. Hence, in contrast to existing work, our approach works without any user interaction and only needs a small amount of traces to derive the indoor map of a building. To demonstrate the performance of MapGENIE, we implemented our system using Android and a foot-mounted IMU to collect traces from volunteers. We show that using our grammar approach, compared to a purely trace-based approach we can identify up to four times as many rooms in a building while at the same time achieving a consistently lower error in the size of detected rooms.","PeriodicalId":263520,"journal":{"name":"2014 IEEE International Conference on Pervasive Computing and Communications (PerCom)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126088657","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: 73

Personalized Energy Auditor: Estimating personal electricity usage 个性化能源审计员:估计个人用电量

2014 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2014-03-24 DOI: 10.1109/PerCom.2014.6813942

Seungwoo Lee, Daye Ahn, Sukjun Lee, Rhan Ha, H. Cha

引用次数: 28