• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

Goodness-of-fit based secure cooperative spectrum sensing for cognitive radio network.

作者信息

Vu-Van Hiep, Koo Insoo

机构信息

The School of Electrical Engineering, University of Ulsan, San 29, Muger 2-dong, Ulsan 680-749, Republic of Korea.

出版信息

ScientificWorldJournal. 2014;2014:752507. doi: 10.1155/2014/752507. Epub 2014 May 18.

DOI:10.1155/2014/752507
PMID:24959626
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4052467/
Abstract

Cognitive radio (CR) is a promising technology for improving usage of frequency band. Cognitive radio users (CUs) are allowed to use the bands without interference in operation of licensed users. Reliable sensing information about status of licensed band is a prerequirement for CR network. Cooperative spectrum sensing (CSS) is able to offer an improved sensing reliability compared to individual sensing. However, the sensing performance of CSS can be destroyed due to the appearance of some malicious users. In this paper, we propose a goodness-of-fit (GOF) based cooperative spectrum sensing scheme to detect the dissimilarity between sensing information of normal CUs and that of malicious users, and reject their harmful effect to CSS. The empirical CDF will be used in GOF test to determine the measured distance between distributions of observation sample set according to each hypothesis of licensed user signal. Further, the DS theory is used to combine results of multi-GOF tests. The simulation results demonstrate that the proposed scheme can protect the sensing process against the attack from malicious users.

摘要

相似文献

1
Goodness-of-fit based secure cooperative spectrum sensing for cognitive radio network.
ScientificWorldJournal. 2014;2014:752507. doi: 10.1155/2014/752507. Epub 2014 May 18.
2
History based forward and feedback mechanism in cooperative spectrum sensing including malicious users in cognitive radio network.认知无线电网络中包含恶意用户的协作频谱感知中基于历史的前馈和反馈机制。
PLoS One. 2017 Aug 18;12(8):e0183387. doi: 10.1371/journal.pone.0183387. eCollection 2017.
3
Secure cooperative spectrum sensing for the cognitive radio network using nonuniform reliability.使用非均匀可靠性的认知无线电网络安全协作频谱感知
ScientificWorldJournal. 2014;2014:101809. doi: 10.1155/2014/101809. Epub 2014 Sep 11.
4
Cooperative spectrum sensing schemes with the interference constraint in cognitive radio networks.认知无线电网络中具有干扰约束的协作频谱感知方案
Sensors (Basel). 2014 May 5;14(5):8037-56. doi: 10.3390/s140508037.
5
Adaptive Trust Threshold Model Based on Reinforcement Learning in Cooperative Spectrum Sensing.基于强化学习的协作频谱感知自适应信任门限模型。
Sensors (Basel). 2023 May 14;23(10):4751. doi: 10.3390/s23104751.
6
A Quantization-Based Multibit Data Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks.一种用于认知无线电网络中协作频谱感知的基于量化的多比特数据融合方案。
Sensors (Basel). 2018 Feb 6;18(2):473. doi: 10.3390/s18020473.
7
A Novel Prediction Model for Malicious Users Detection and Spectrum Sensing Based on Stacking and Deep Learning.基于堆叠和深度学习的恶意用户检测和频谱感知新预测模型。
Sensors (Basel). 2022 Aug 28;22(17):6477. doi: 10.3390/s22176477.
8
Securing Cooperative Spectrum Sensing Against Collusive SSDF Attack using XOR Distance Analysis in Cognitive Radio Networks.在认知无线电网络中使用异或距离分析防范针对勾结式频谱感知数据伪造攻击的协作频谱感知
Sensors (Basel). 2018 Jan 27;18(2):370. doi: 10.3390/s18020370.
9
Deep Cooperative Spectrum Sensing Based on Residual Neural Network Using Feature Extraction and Random Forest Classifier.基于特征提取和随机森林分类器的残差神经网络的深度协作频谱感知。
Sensors (Basel). 2021 Oct 28;21(21):7146. doi: 10.3390/s21217146.
10
A Novel Semi-Soft Decision Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks.一种用于认知无线电网络中协作频谱感知的新型半软判决方案。
Sensors (Basel). 2019 Jun 2;19(11):2522. doi: 10.3390/s19112522.