The 25th Annual International Conference on Mobile Computing and Networking最新文献_第6页

Canceling Inaudible Voice Commands Against Voice Control Systems 针对语音控制系统取消听不清的语音命令

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3345429

Yitao He, Junyu Bian, Xinyu Tong, Zihui Qian, Wei Zhu, Xiaohua Tian, Xinbing Wang

{"title":"Canceling Inaudible Voice Commands Against Voice Control Systems","authors":"Yitao He, Junyu Bian, Xinyu Tong, Zihui Qian, Wei Zhu, Xiaohua Tian, Xinbing Wang","doi":"10.1145/3300061.3345429","DOIUrl":"https://doi.org/10.1145/3300061.3345429","url":null,"abstract":"Recent studies show that the voice control system (VCS) is subject to the inaudible voice command attack, which can not be heard by human ears but can be recorded by the microphone. An adversary could leverage the attack to disable the VCS user's home security system, leak the victim's privacy or download malware stealthily. Efforts have been dedicated to developing forensics based defense mechanisms, which target at detecting traces of the attack signal; however, we find that existing approaches of the kind still leave loopholes. Moreover, a complete defense mechanism should be able to not only detect the attack but also cancel out the attack signal, and meanwhile ensure the legitimate voice commands unaffected, which however is still unavailable to the best of our knowledge. This paper is an attempt to fill the gap. We first systematically analyze existing forensics based defense mechanisms and reveal the root cause of their loopholes. Then we present an active inaudible-voice-command cancellation (AIC) design, which can reliably detect and capture the attack signal facilitated by our custom-designed \"guard'' signal transmitter. AIC can create a special spectrum in the passband of the VCS microphone, based on which we are able to neutralize the attack signal in software means. We implement a prototype of our defense system and conduct comprehensive experiments to validate our design.","PeriodicalId":223523,"journal":{"name":"The 25th Annual International Conference on Mobile Computing and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131958419","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: 29

Poster: Cross Labelling and Learning Unknown Activities Among Multimodal Sensing Data 海报:在多模态传感数据中交叉标记和学习未知活动

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3343407

Lan Zhang, Daren Zheng, Zhengtao Wu, Mengjing Liu, Mu Yuan, Feng Han, Xiangyang Li

引用次数: 0

FLUID: Flexible User Interface Distribution for Ubiquitous Multi-device Interaction 流体:用于无处不在的多设备交互的灵活用户界面分布

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3345443

Sangeun Oh, Ahyeon Kim, Sunjae Lee, Kilho Lee, Dae R. Jeong, Steven Y. Ko, I. Shin

{"title":"FLUID: Flexible User Interface Distribution for Ubiquitous Multi-device Interaction","authors":"Sangeun Oh, Ahyeon Kim, Sunjae Lee, Kilho Lee, Dae R. Jeong, Steven Y. Ko, I. Shin","doi":"10.1145/3300061.3345443","DOIUrl":"https://doi.org/10.1145/3300061.3345443","url":null,"abstract":"The growing trend of multi-device ownerships creates a need and an opportunity to use applications across multiple devices. However, in general, the current app development and usage still remain within the single-device paradigm, falling far short of user expectations. For example, it is currently not possible for a user to dynamically partition an existing live streaming app with chatting capabilities across different devices, such that she watches her favorite broadcast on her smart TV while real-time chatting on her smartphone. In this paper, we present FLUID, a new Android-based multi-device platform that enables innovative ways of using multiple devices. FLUID aims to i) allow users to migrate or replicate individual user interfaces (UIs) of a single app on multiple devices (high flexibility), ii) require no additional development effort to support unmodified, legacy applications (ease of development), and iii) support a wide range of apps that follow the trend of using custom-made UIs (wide applicability). Previous approaches, such as screen mirroring, app migration, and customized apps utilizing multiple devices, do not satisfy those goals altogether. FLUID, on the other hand, meets the goals by carefully analyzing which UI states are necessary to correctly render UI objects, deploying only those states on different devices, supporting cross-device function calls transparently, and synchronizing the UI states of replicated UI objects across multiple devices. Our evaluation with 20 unmodified, real-world Android apps shows that FLUID can transparently support a wide range of apps and is fast enough for interactive use.","PeriodicalId":223523,"journal":{"name":"The 25th Annual International Conference on Mobile Computing and Networking","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133926681","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: 17

Poster: Understanding Long-Term Mobility and Charging Evolving of Shared EV Networks 海报:了解共享电动汽车网络的长期移动性和充电演变

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3343402

Guang Wang, Desheng Zhang

引用次数: 3

HotEdgeVideo'19: Workshop on Hot Topics in Video Analytics and Intelligent Edges HotEdgeVideo'19:视频分析和智能边缘热点话题研讨会

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3355630

G. Ananthanarayanan, Yunxin Liu, Yuanchao Shu

引用次数: 0

Fast and Efficient Cross Band Channel Prediction Using Machine Learning 使用机器学习快速有效的跨频带信道预测

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3345438

Arjun Bakshi, Yifan Mao, K. Srinivasan, S. Parthasarathy

{"title":"Fast and Efficient Cross Band Channel Prediction Using Machine Learning","authors":"Arjun Bakshi, Yifan Mao, K. Srinivasan, S. Parthasarathy","doi":"10.1145/3300061.3345438","DOIUrl":"https://doi.org/10.1145/3300061.3345438","url":null,"abstract":"Channel information plays an important role in modern wireless communication systems. Systems that use different frequency bands for uplink and downlink communication often need feedback between devices to exchange band specific channel information. The current state-of-the-art approach proposes a way to predict the channel in the downlink based on that of the observed uplink by identifying variables underlying the uplink channel. In this paper we present a solution that greatly reduces the complexity of this task, and is even applicable for single antenna devices. Our approach uses a neural network trained on a standard channel model to generate coarse estimates for the variables underlying the channel. We then use a simple and efficient single antenna optimization framework to get more accurate variable estimates, which can be used for downlink channel prediction. We implement our approach on software defined radios and compare it to the state-of-the-art through experiments and simulations. Results show that our approach reduces the time complexity by at least an order of magnitude (10x), while maintaining similar prediction quality.","PeriodicalId":223523,"journal":{"name":"The 25th Annual International Conference on Mobile Computing and Networking","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114459514","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: 16

Poster: A Linear Programming Approach for SFC Placement in Mobile Edge Computing 海报:移动边缘计算中SFC放置的线性规划方法

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3343394

Mei Wang, B. Cheng, Junliang Chen

引用次数: 2

Poster: Inaudible High-throughput Communication Through Acoustic Signals 海报:通过声学信号进行高通量通信

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3343405

Yang Bai, Jian Liu, Yingying Chen, Li Lu, Jiadi Yu

引用次数: 2

AMP up your Mobile Web Experience: Characterizing the Impact of Google's Accelerated Mobile Project AMP提升你的移动网络体验:描述谷歌加速移动项目的影响

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3300137

Byungjin Jun, F. Bustamante, Sung Yoon Whang, Zachary S. Bischof

{"title":"AMP up your Mobile Web Experience: Characterizing the Impact of Google's Accelerated Mobile Project","authors":"Byungjin Jun, F. Bustamante, Sung Yoon Whang, Zachary S. Bischof","doi":"10.1145/3300061.3300137","DOIUrl":"https://doi.org/10.1145/3300061.3300137","url":null,"abstract":"The rapid growth in the number of mobile devices, subscriptions and their associated traffic, has served as motivation for several projects focused on improving mobile users' quality of experience (QoE). Few have been as contentious as the Google-initiated Accelerated Mobile Project (AMP), both praised for its seemingly instant mobile web experience and criticized based on concerns about the enforcement of its formats. This paper presents the first characterization of AMP's impact on users' QoE. We do this using a corpus of over 2,100 AMP webpages, and their corresponding non-AMP counterparts, based on trendy-keyword-based searches. We characterized AMP's impact looking at common web QoE metrics, including Page Load Time, Time to First Byte and SpeedIndex (SI). Our results show that AMP significantly improves SI, yielding on average a 60% lower SI than non-AMP pages without accounting for prefetching. Prefetching of AMP pages pushes this advantage even further, with prefetched pages loading over 2,000ms faster than non-prefetched AMP pages. This clear boost may come, however, at a non-negligible cost for users with limited data plans as it incurs an average of over 1.4~MB of additional data downloaded, unbeknownst to users.","PeriodicalId":223523,"journal":{"name":"The 25th Annual International Conference on Mobile Computing and Networking","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128879426","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: 24

Source Compression with Bounded DNN Perception Loss for IoT Edge Computer Vision 基于有界DNN感知损失的物联网边缘计算机视觉源压缩

The 25th Annual International Conference on Mobile Computing and Networking Pub Date : 2019-08-05 DOI: 10.1145/3300061.3345448

Xiufeng Xie, Kyu-Han Kim

{"title":"Source Compression with Bounded DNN Perception Loss for IoT Edge Computer Vision","authors":"Xiufeng Xie, Kyu-Han Kim","doi":"10.1145/3300061.3345448","DOIUrl":"https://doi.org/10.1145/3300061.3345448","url":null,"abstract":"IoT and deep learning based computer vision together create an immense market opportunity, but running deep neural networks (DNNs) on resource-constrained IoT devices remains challenging. Offloading DNN inference to an edge server is a promising solution, but limited wireless bandwidth bottlenecks its end-to-end performance and scalability. While IoT devices can adopt source compression to cope with the limited bandwidth, existing compression algorithms (or codecs) are not designed for DNN (but for human eyes), and thus, suffer from either low compression rates or high DNN inference errors. This paper presents GRACE, a DNN-aware compression algorithm that facilitates the edge inference by significantly saving the network bandwidth consumption without disturbing the inference performance. Given a target DNN, GRACE (i) analyzes DNN's perception model w.r.t both spatial frequencies and colors and (ii) generates an optimized compression strategy for the model -- one-time offline process. Next, GRACE deploys thus-generated compression strategy at IoT devices (or source) to perform online source compression within the existing codec framework, adding no extra overhead. We prototype GRACE on JPEG (the most popular image codec framework), and our evaluation results show that GRACE indeed achieves the superior compression performance over existing strategies for key DNN applications. For semantic segmentation tasks, GRACE reduces a source size by 23% compared to JPEG with similar interference accuracy (0.38% lower than GRACE). Further, GRACE even achieves 7.5% higher inference accuracy than JPEG with a commonly used quality level of 75 does. For classification tasks, GRACE reduces the bandwidth consumption by 90% over JPEG with the same inference accuracy.","PeriodicalId":223523,"journal":{"name":"The 25th Annual International Conference on Mobile Computing and Networking","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127976396","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: 46