2022 International Conference on Networking and Network Applications (NaNA)最新文献_第6页

Multi-RIS Deployment for High Data-Rate Communications 高数据速率通信的多ris部署

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00076

Muhammad Fawad Khan, Haoran Mei, Shahnila Rahim, Limei Peng, P. Ho

引用次数: 1

Feature Extraction and Identification of Specific Radiation Sources Based on Axial Integral Bispectrum and Deep Residual Shrinkage Network 基于轴向积分双谱和深度残余收缩网络的特定辐射源特征提取与识别

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00010

Yifan Li, Chunjie Cao, Hong Zhang, Xiuhua Wen, Yang Sun, Keqi Zhan

{"title":"Feature Extraction and Identification of Specific Radiation Sources Based on Axial Integral Bispectrum and Deep Residual Shrinkage Network","authors":"Yifan Li, Chunjie Cao, Hong Zhang, Xiuhua Wen, Yang Sun, Keqi Zhan","doi":"10.1109/NaNA56854.2022.00010","DOIUrl":"https://doi.org/10.1109/NaNA56854.2022.00010","url":null,"abstract":"In the existing research on the identification of specific radiation sources, some noise inevitably occurs when classifying samples, which affects the extraction of Radio frequency fingerprint (RFF) with unique native properties, thus reducing the classification accuracy. In this paper, a feature extraction and identification method for specific radiation sources based on the integration of axial integral bispectrum features and deep residual shrinkage networks(DRSN) is proposed. First, the axial integral bispectrum is used to extract the signal features, and then the signal is denoised by soft thresholding in the deep residual shrinkage network, and the threshold is automatically set according to the situation of each sample using the attention mechanism. The experimental results show that the new method can effectively improve the classification accuracy under low signal-to-noise ratio, and in the case of low signal-to-noise ratio, the maximum distance of 62ft can achieve 98.5% classification and recognition accuracy.","PeriodicalId":113743,"journal":{"name":"2022 International Conference on Networking and Network Applications (NaNA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123037187","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: 1

3D Deployment of UAVs for Communications under Multiple Eavesdroppers 多窃听器下无人机通信的三维部署

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00081

Ke Zhao, Mian Muaz Razaq, Kaixin Li, Limei Peng, P. Ho

引用次数: 0

Partial Computation Offloading and Resource Allocation via Deep Deterministic Policy Gradient 基于深度确定性策略梯度的部分计算卸载与资源分配

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00070

Yingxin Shan, Peng Liao, Zhuo Wang, Lin An

引用次数: 0

Research on Intrusion Detection Algorithm Based on Optimized CNN-LSTM 基于优化CNN-LSTM的入侵检测算法研究

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00024

J. Du, Yang Kai, Zhentao Huang, Lin Jiang, Huang Lei, Haixia Yu

{"title":"Research on Intrusion Detection Algorithm Based on Optimized CNN-LSTM","authors":"J. Du, Yang Kai, Zhentao Huang, Lin Jiang, Huang Lei, Haixia Yu","doi":"10.1109/NaNA56854.2022.00024","DOIUrl":"https://doi.org/10.1109/NaNA56854.2022.00024","url":null,"abstract":"With the development of computer network technology, network security has become more and more important, and intrusion detection has become an important means of network attack detection. In recent years, machine learning has played an irreplaceable role in many fields. In order to improve the accuracy of intrusion detection, many machine learning algorithms have been applied in intrusion detection models. Through the learning of training samples in KDDCUP99 intrusion data, this paper uses the relevant theory of neural network to construct an intrusion detection classification model based on optimized convolutional neural network and long short-term memory network, which is used to distinguish between normal state and various intrusion states. Convolutional neural networks, deep neural networks and traditional decision tree algorithms are compared in details in terms of accuracy and loss. The experimental results show that the prediction accuracy of the algorithm proposed in this paper is 0.972, and the test loss is 0.045, which effectively improves the classification accuracy of intrusion detection. Finally, the future development direction and prospects of the algorithm are prospected to further improve the security of computer networks.","PeriodicalId":113743,"journal":{"name":"2022 International Conference on Networking and Network Applications (NaNA)","volume":"603 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116350726","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: 2

A Cache-enabled NDN Forwarding Plane based on Programmable Switches 基于可编程交换机支持缓存的NDN转发平面

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00033

Lei Yu, Shuai Gao, Ningchun Liu, Hongchao Wang, Wei Su

引用次数: 0

A Privacy-Preserving Gait Recognition Scheme Under Homomorphic Encryption 一种同态加密下的隐私保护步态识别方案

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00075

Leyu Lin, Bo Tian, Yue Zhao, Yiru Niu

引用次数: 1

Block-Streaming Service Loading Optimization of Android Dalvik Executable File for Cloud-End Collaboration 面向云端协作的Android Dalvik可执行文件块流服务加载优化

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00055

Yichuan Wang, Yanhua Feng, Yanning Du, X. Hei, Yuying Tian, Xiangjie Cui

{"title":"Block-Streaming Service Loading Optimization of Android Dalvik Executable File for Cloud-End Collaboration","authors":"Yichuan Wang, Yanhua Feng, Yanning Du, X. Hei, Yuying Tian, Xiangjie Cui","doi":"10.1109/NaNA56854.2022.00055","DOIUrl":"https://doi.org/10.1109/NaNA56854.2022.00055","url":null,"abstract":"In recent years, dynamic loading technologies of Android applications have emerged in an endless stream. At present, the existing Android application loading method is to load the entire Android Dalvik Executable (DEX) file for cloud-end collaboration, and there is a problem of finer-grained loading optimization in the loading process. Based on the analysis of Android DEX file in this paper, a formal model of each class is established by using the analysis result of this file, analyzes the user's behavior, and tries to ensure that the class to be used in high probability is loaded into memory first, and a block-streaming service loading optimization model of Android DEX file is put forward. The validity of the model is verified by quantitative analysis of Android DEX file. Trying to load the whole Dalvik Executable file and the classes needed by the application separately, recording and comparing the storage space and loading time overhead. In order to avoid the uncertain factors of the network environment, the above files have been tested and recorded several times. The result shows that the time and storage space for loading the whole DEX file are far greater than the sum of the classes required by the application. With this model, the fine-grained formal analysis of Android DEX file can be performed, which is of great significance for exploring the loading method of application block flow service.","PeriodicalId":113743,"journal":{"name":"2022 International Conference on Networking and Network Applications (NaNA)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115748061","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: 0

UAV-mounted Intelligent Reflecting Surface (IRS) MISO Communications 安装在无人机上的智能反射面(IRS) MISO通信

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00019

Kaixin Li, Ke Zhao, Muhammad Fawad Khan, P. Ho, Limei Peng

引用次数: 1

Channel Capacity Analysis for Diffusive Molecular Communication with a Partly Covered Comprehensive Reactive Receiver 部分覆盖的综合反应接收器扩散分子通信的信道容量分析

2022 International Conference on Networking and Network Applications (NaNA) Pub Date : 2022-12-01 DOI: 10.1109/NaNA56854.2022.00015

Junning Zhu, Xuening Liao, Zhenqiang Wu

引用次数: 0