2018 IEEE/ACM Symposium on Edge Computing (SEC)最新文献

Aggio: A Coupon Safe for Privacy-Preserving Smart Retail Environments Aggio:用于保护隐私的智能零售环境的优惠券安全

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00020

A. Harris, Robin Snader, R. Kravets

{"title":"Aggio: A Coupon Safe for Privacy-Preserving Smart Retail Environments","authors":"A. Harris, Robin Snader, R. Kravets","doi":"10.1109/SEC.2018.00020","DOIUrl":"https://doi.org/10.1109/SEC.2018.00020","url":null,"abstract":"Researchers and industry experts are looking at how to improve a shopper's experience and a store's revenue by leveraging and integrating technologies at the edges of the network, such as Internet-of-Things (IoT) devices, cloud-based systems, and mobile applications. The integration of IoT technology can now be used to improve purchasing incentives through the use of electronic coupons. Research has shown that targeted electronic coupons are the most effective and coupons presented to the shopper when they are near the products capture the most shoppers' dollars. Although it is easy to imagine coupons being broadcast to a shopper's mobile device over a low-power wireless channel, such a solution must be able to advertise many products, target many individual shoppers, and at the same time, provide shoppers with their desired level of privacy. To support this type of IoT-enabled shopping experience, we have designed Aggio, an electronic coupon distribution system that enables the distribution of localized, targeted coupons while supporting user privacy and security. Aggio uses cryptographic mechanisms to not only provide security but also to manage shopper groups e.g., bronze, silver, and gold reward programs) and minimize resource usage, including bandwidth and energy. The novel use of cryptographic management of coupons and groups allows Aggio to reduce bandwidth use, as well as reduce the computing and energy resources needed to process incoming coupons. Through the use of local coupon storage on the shopper's mobile device, the shopper does not need to query the cloud and so does not need to expose all of the details of their shopping decisions. Finally, the use of privacy preserving communication between the shopper's mobile device and the CouponHubs that are distributed throughout the retail environment allows the shopper to expose their location to the store without divulging their location to all other shoppers present in the store.","PeriodicalId":376439,"journal":{"name":"2018 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121918040","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: 5

Demo: ThingsMigrate - Platform-Independent Live-Migration of JavaScript Processes 演示:ThingsMigrate——JavaScript进程的独立于平台的实时迁移

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00044

Kumseok Jung, Julien Gascon-Samson, K. Pattabiraman

引用次数: 1

Vigilia: Securing Smart Home Edge Computing Vigilia:保护智能家居边缘计算

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00013

R. Trimananda, Ali Younis, Bojun Wang, Bin Xu, Brian Demsky, G. Xu

引用次数: 34

FastPay: A Secure Fast Payment Method for Edge-IoT Platforms using Blockchain 快速支付：使用区块链的边缘物联网平台安全快速支付方法

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00055

Zijiang Hao, Raymond Ji, Qun A. Li

引用次数: 17

Edge-Based Discovery of Training Data for Machine Learning 基于边缘的机器学习训练数据发现

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00018

Ziqiang Feng, S. George, J. Harkes, P. Pillai, R. Klatzky, M. Satyanarayanan

引用次数: 15

Smart Surveillance as an Edge Service for Real-Time Human Detection and Tracking 智能监控作为实时人员检测和跟踪的边缘服务

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00036

S. Nikouei, Yu Chen, Timothy R. Faughnan

引用次数: 9

EveryLite: A Lightweight Scripting Language for Micro Tasks in IoT Systems EveryLite:物联网系统中微任务的轻量级脚本语言

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00050

Zhenying Li, Xiaohui Peng, Lu Chao, Zhiwei Xu

引用次数: 14

SafeShareRide: Edge-Based Attack Detection in Ridesharing Services SafeShareRide:基于边缘的拼车服务攻击检测

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00009

Liangkai Liu, Xingzhou Zhang, Mu Qiao, Weisong Shi

{"title":"SafeShareRide: Edge-Based Attack Detection in Ridesharing Services","authors":"Liangkai Liu, Xingzhou Zhang, Mu Qiao, Weisong Shi","doi":"10.1109/SEC.2018.00009","DOIUrl":"https://doi.org/10.1109/SEC.2018.00009","url":null,"abstract":"Ridesharing services, such as Uber and Didi, are enjoying great popularity; however, a big challenge remains in guaranteeing the safety of passenger and driver. State-of-the-art work has primarily adopted the cloud model, where data collected through end devices on vehicles are uploaded to and processed in the cloud. However, data such as video can be too large to be uploaded onto the cloud in real time. When a vehicle is moving, the network communication can become unstable, leading to high latency for data uploading. In addition, the cost of huge data transfer and storage is a big concern from a business point of view. As edge computing enables more powerful computing end devices, it is possible to design a latency-guaranteed framework to ensure in-vehicle safety. In this paper, we propose an edge-based attack detection in ridesharing services, namely SafeShareRide, which can detect dangerous events happening in the vehicle in near real time. SafeShareRide is implemented on both drivers' and passengers' smartphones. The detection of SafeShareRide consists of three stages: speech recognition, driving behavior detection, and video capture and analysis. Abnormal events detected during the stages of speech recognition or driving behavior detection will trigger the video capture and analysis in the third stage. The video data processing is also redesigned: video compression is conducted at the edge to save upload bandwidth while video analysis is conducted in the cloud. We implement the SafeShareRide system by leveraging open source algorithms. Our experiments include a performance comparison between SafeShareRide and other edge-based and cloud-based approaches, CPU usage and memory usage of each detection stage, and a performance comparison between stationary and moving scenarios. Finally, we summarize several insights into smartphone based edge computing systems.","PeriodicalId":376439,"journal":{"name":"2018 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127506751","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: 32

Poster: Towards a Distributed and Self-Adaptable Cloud-Edge Middleware 海报:走向分布式和自适应的云边缘中间件

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00037

Julien Gascon-Samson, Kumseok Jung, K. Pattabiraman

引用次数: 4

Extend Cloud to Edge with KubeEdge 使用KubeEdge将云扩展到边缘

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00048

Ying Xiong, Yulin Sun, Li Xing, Ying Huang

{"title":"Extend Cloud to Edge with KubeEdge","authors":"Ying Xiong, Yulin Sun, Li Xing, Ying Huang","doi":"10.1109/SEC.2018.00048","DOIUrl":"https://doi.org/10.1109/SEC.2018.00048","url":null,"abstract":"In this paper, we introduce an infrastructure in edge computing environment, KubeEdge, to extend cloud capabilities to the edge. In the new form of cloud architecture, Cloud consists of computing resources both at centralized data centers and at distributed edges. KubeEdge infrastructure connects and coordinates two computing environments for applications leveraging both computing resources to achieve better performance and user experience. Technically, KubeEdge provides the network protocol infrastructure and the same runtime environment on the edge as in the cloud, which allows the seamless communication of applications with components running on edge nodes as well as cloud servers. It also allows the existing cloud services and cloud development model to be adopted at edge. Based on Kubernetes [1], KubeEdge architecture includes a network protocol stack called KubeBus, a distributed metadata store and synchronization service, and a lightweight agent (EdgeCore) for the edge. KubeBus is designed to have its own implementation of OSI network protocol layers, which connects servers at edge and VMs in the cloud as one virtual network. KubeBus provides a unified multitenant communication infrastructure with fault tolerance and high availability. The distributed metadata store and sync service is designed to support the offline scenario when edge nodes are not connected to the cloud. EdgeController component in KubeEdge architecture is a controller plugin for Kubernetes [1] to manage remote edge nodes and cloud VMs as one logical cluster, which enables KubeEdge to schedule, deploy and manage container applications across edge and cloud with the same API.","PeriodicalId":376439,"journal":{"name":"2018 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121500998","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: 104