2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)最新文献_第7页

Secure Authentication in Cross-Technology Communication for Heterogeneous IoT 异构物联网跨技术通信中的安全认证

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935663

Sihan Yu, Xiaonan Zhang, Pei Huang, Linke Guo

引用次数: 8

Finding a ‘New’ Needle in the Haystack: Unseen Radio Detection in Large Populations Using Deep Learning 在干草堆中寻找“新”针:使用深度学习在大量人群中进行看不见的无线电探测

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935862

Andrey Gritsenko, Zifeng Wang, T. Jian, Jennifer G. Dy, K. Chowdhury, Stratis Ioannidis

{"title":"Finding a ‘New’ Needle in the Haystack: Unseen Radio Detection in Large Populations Using Deep Learning","authors":"Andrey Gritsenko, Zifeng Wang, T. Jian, Jennifer G. Dy, K. Chowdhury, Stratis Ioannidis","doi":"10.1109/DySPAN.2019.8935862","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935862","url":null,"abstract":"Radio frequency fingerprinting enhances security and privacy of wireless networks and communications by learning and extracting unique characteristics embedded in transmitted signals. Deep learning-based approaches learn radio fingerprints without hand-engineering features. One persisting drawback in deep learning methods is they identify only devices that are previously observed in a training set: if a radio signal from a new, unseen, device is passed through the classifier, the source device will be classified as one of the known devices. We propose a novel approach that facilitates new class detection without retraining a neural network, and perform extensive analysis of the proposed model both in terms of model parameters and real-world datasets. We accomplish this by first breaking down a longer transmission burst into smaller slices, and assessing classifier confidence on a new transmission based on per slice statistics: our approach detects a new device with 76% accuracy, while reducing the classification accuracy of 500 previously seen devices by no more than 10%.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125284882","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

A Case Study of Spectrum Analysis Using Unsupervised Machine Learning 使用无监督机器学习的频谱分析案例研究

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935714

Vaishali Nagpure, Stephanie Vaccaro, C. Hood

引用次数: 0

Exploiting In-building Small Cell Architecture for Realizing Dynamic Spectrum Sharing Techniques 利用楼内小蜂窝结构实现动态频谱共享技术

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935772

Rony Kumer Saha

引用次数: 2

On Degrees of Freedom for Multi-user Interweave and Underlay Cognitive Radios 多用户交织和底层认知无线电的自由度研究

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935801

Dongming Li, Deng-yin Zhang, Gengxin Zhang

引用次数: 0

Crowdsensing Based Spectrum Database with Total Variation Regularization 基于群体感知的全变分正则化频谱数据库

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935664

Katsuya Suto, Riku Hashimoto

引用次数: 0

PriRoster: Privacy-preserving Radio Context Attestation in Cognitive Radio Networks 认知无线电网络中保护隐私的无线电上下文认证

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935740

Ruide Zhang, Ning Wang, Ning Zhang, Zheng Yan, W. Lou, Yiwei Thomas Hou

{"title":"PriRoster: Privacy-preserving Radio Context Attestation in Cognitive Radio Networks","authors":"Ruide Zhang, Ning Wang, Ning Zhang, Zheng Yan, W. Lou, Yiwei Thomas Hou","doi":"10.1109/DySPAN.2019.8935740","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935740","url":null,"abstract":"Spectrum shortage is a global concern and cognitive radio network (CRN) is envisioned to be one of the key technologies for overcoming this challenge. However, proper operation of a CRN heavily depends on compliance of cognitive radios (CRs). Although remote attestation of a CR’s radio context is a promising solution, current remote attestation that requires the target’s configuration to be publicly available to the verifier poses a fundamental challenge to the operational security of spectrum users, especially military primary users. To protect a device’s configuration information, we propose PriRoster, a privacy-preserving remote attestation mechanism, that effectively separates the need to know the operational configuration from the capability to execute the verification process correctly at the verifier. PriRoster hides sensitive device and/or radio configuration information from untrusted intermediate verifiers in a public network and enables a range of new applications such as efficient network-wide radio context attestation. Trusted execution environment (TEE) such as Intel SGX is used in our design to provide confidential processing. However, naive application of TEE suffers from not only poor system scalability, but also information side channel leakage. We develop trust transfer protocol to significantly enhance system scalability, and the protection against information side channel attack is accomplished by automatically incorporating obliviousness primitive into the attestation program. We build a prototype of the proposed PriRoster system using Raspberry Pi, USRP, Intel NUC, and AWS cloud. The feasibility of our proposed framework is demonstrated by system benchmarks and the effectiveness of the proposed oblivious appraisal functions are verified by recording memory access pattern via code instrumentation.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128303801","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

EyeLoc: Smartphone Vision Enabled Plug-n-play Indoor Localization in Large Shopping Malls eyeoc:大型购物中心的智能手机视觉即插即用室内定位

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935776

Zhichao Cao, Jialuo Du, Manni Liu, Qing Zhou

{"title":"EyeLoc: Smartphone Vision Enabled Plug-n-play Indoor Localization in Large Shopping Malls","authors":"Zhichao Cao, Jialuo Du, Manni Liu, Qing Zhou","doi":"10.1109/DySPAN.2019.8935776","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935776","url":null,"abstract":"Indoor localization is an emerging demand in many large shopping malls. Existing indoor localization systems, however, require exhausted system bootstrap and calibration phases. The huge sunk cost usually hinders practical deployment of the indoor localization systems in large shopping malls. In contrast, we observe that floor-plan images of large shopping malls, which highlight the positions of many shops, are widely available in Google Maps, Gaode Maps, Baidu Maps etc. According to several observed shops, people can localize themselves (self-localization). However, due to the requirements of geometric sense and space transformation, not all people get used to this way. In this paper, we propose EyeLoc, which uses smartphone vision to enable accurate self-localization on floor-plan images. EyeLoc addresses several challenges which include developing ubiquitous smartphone vision system, efficient vision clue extraction and robust measurement error mitigation. We implement EyeLoc in Android and evaluate its performance in emulated environment and four large shopping malls. The 90-percentile errors of localization and heading direction are 4m and 20○ in the two large shopping malls.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121470861","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: 3

Team Zylinium DARPA Spectrum Collaboration Challenge Radio Design and Implementation

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935729

R. Baxley, R. S. Thompson

引用次数: 2

Software-defined Radios to Accelerate mmWave Wireless Innovation 软件定义无线电加速毫米波无线创新

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935877

Kai Zheng, J. Jornet, Michele Polese, M. Zorzi, Jim Buckwalter, M. Rodwell, S. Mandal, Xin Wang, Jaakko Haarla, V. Semkin, Aditya Dhananjay, M. Mezzavilla, A. Madanayake, S. Bhardwaj, V. Ariyarathna, A. Gosain, T. Melodia, Francesco Restuccia

引用次数: 8