Lars Baumgärtner, Pablo Graubner, Nils Schmidt, Bernd Freisleben
{"title":"Andro Lyze: A Distributed Framework for Efficient Android App Analysis","authors":"Lars Baumgärtner, Pablo Graubner, Nils Schmidt, Bernd Freisleben","doi":"10.1109/MobServ.2015.20","DOIUrl":"https://doi.org/10.1109/MobServ.2015.20","url":null,"abstract":"In recent years, the number of mobile applications has grown significantly. Not surprisingly, various security and privacy concerns associated with mobile applications have emerged. Several researchers are addressing these problems by analyzing the security properties of mobile application code. Most of the security checks rely on custom scripts and are quite heterogeneous with respect to dependencies, deployment and reporting. In this paper, we present AndroLyze, a distributed framework with unified logging and reporting functionality to perform security checks on large numbers of applications in an efficient manner. AndroLyze provides optimized scheduling algorithms for distributing static code analysis tasks across several machines. Moreover, AndroLyze can handle several versions of a single mobile application to generate a security track record over many versions. To demonstrate the benefits of AndroLyze, we have analyzed the Top Free 500 Android applications of all categories in Google Play collected over three years. The resulting data set consists of almost 40,000 mobile applications and requires about 227 GB of storage space.","PeriodicalId":166267,"journal":{"name":"2015 IEEE International Conference on Mobile Services","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127734735","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":"Orientational Spatial Part Modeling for Fine-Grained Visual Categorization","authors":"Hantao Yao, Shiliang Zhang, Fei Xie, Yongdong Zhang, Dongming Zhang, Yu Su, Q. Tian","doi":"10.1109/MobServ.2015.56","DOIUrl":"https://doi.org/10.1109/MobServ.2015.56","url":null,"abstract":"Although significant success has been achieved in fine-grained visual categorization, most of existing methods require bounding boxes or part annotations for training and test, resulting in limited usability and flexibility. To conquer these limitations, we aim to automatically detect the bounding box and parts for fine-grained object classification. The bounding boxes are acquired by a transferring strategy which infers the locations of objects from a set of annotated training images. Based on the generated bounding box, we propose a multiple-layer Orientational Spatial Part (OSP) model to generate a refined description for the object. Finally, we employ the output of deep Convolutional Neural Network (dCNN) as the feature and train a linear SVM as object classifier. Extensive experiments on public benchmark datasets manifest the impressive performance of our method, i.e., Classification accuracy achieves 63.9% on CUB-200-2011 and 75.6% on Aircraft, which are actually higher than many existing methods using manual annotations.","PeriodicalId":166267,"journal":{"name":"2015 IEEE International Conference on Mobile Services","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129120227","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}
Wenbing Zhao, D. Deborah, M. A. Reinthal, B. Ekelman, Glenn Goodman, Joan E. Niederriter
{"title":"Privacy-Aware Human Motion Tracking with Realtime Haptic Feedback","authors":"Wenbing Zhao, D. Deborah, M. A. Reinthal, B. Ekelman, Glenn Goodman, Joan E. Niederriter","doi":"10.1109/MobServ.2015.67","DOIUrl":"https://doi.org/10.1109/MobServ.2015.67","url":null,"abstract":"In this paper, we describe a system that integrates 3D motion sensors, wearable devices, and smart phones to perform privacy-aware human motion tracking with real time hap tic feedback. The system is designed to enhance safe patient handling and thus reduce the injury rates of health caregivers in nursing homes and hospitals. Due to privacy concern and governmental regulations, it is paramount that only consented caregivers are tracked. Our system satisfies this requirement by employing a registration process for consented caregivers before their activities are monitored. The registration process involves the corroboration of human motion captured in different modalities (computer-vision-based and accelerometer-based). Patient handling activities of caregivers are assessed in real time using a rule-based approach. Upon detection of unsafe activities, hap tic feedback is delivered in real time to the caregiver via the wearable device worn by the caregiver.","PeriodicalId":166267,"journal":{"name":"2015 IEEE International Conference on Mobile Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131275828","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":"Semantic Gateway as a Service Architecture for IoT Interoperability","authors":"Pratikkumar Desai, A. Sheth, Pramod Anantharam","doi":"10.1109/MobServ.2015.51","DOIUrl":"https://doi.org/10.1109/MobServ.2015.51","url":null,"abstract":"The Internet of Things (IoT) is set to occupy a substantial component of future Internet. The IoT connects sensors and devices that record physical observations to applications and services of the Internet[1]. As a successor to technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has stumbled into vertical silos of proprietary systems, providing little or no interoperability with similar systems. As the IoT represents future state of the Internet, an intelligent and scalable architecture is required to provide connectivity between these silos, enabling discovery of physical sensors and interpretation of messages between the things. This paper proposes a gateway and Semantic Web enabled IoT architecture to provide interoperability between systems, which utilizes established communication and data standards. The Semantic Gateway as Service (SGS) allows translation between messaging protocols such as XMPP, CoAP and MQTT via a multi-protocol proxy architecture. Utilization of broadly accepted specifications such as W3Cs Semantic Sensor Network (SSN) ontology for semantic annotations of sensor data provide semantic interoperability between messages and support semantic reasoning to obtain higher-level actionable knowledge from low-level sensor data.","PeriodicalId":166267,"journal":{"name":"2015 IEEE International Conference on Mobile Services","volume":"1016 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120876868","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}