An Online Learning Approach for Cooperator Selection in CSS Under SSDF Attack
Author:
Affiliation:
1. School of Aerospace, Xihua University, Chengdu, China
2. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
Funder
Central Government Guide Local Science and Technology Development Funds
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation
Link
http://xplorestaging.ieee.org/ielx7/4234/9826535/09771403.pdf?arnumber=9771403
Reference16 articles.
1. On the Selection of the Best Detection Performance Sensors for Cognitive Radio Networks
2. Ensemble Learning Based Robust Cooperative Sensing in Full-Duplex Cognitive Radio Networks
3. Leveraging Online Learning for CSS in Frugal IoT Network
4. Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack
5. Dynamic cooperator selection in cognitive radio networks
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Dynamic sliding window‐cooperative spectrum sensing against massive SSDF attack in interweave cognitive internet of things;Transactions on Emerging Telecommunications Technologies;2024-03
2. Energy-Aware Cooperative Spectrum Sensing Under Ignorance on Internet of Mobile Things;IEEE Open Journal of the Communications Society;2024
3. Defending Cooperative Spectrum Sensing From Byzantine Attacks: An Effective Entropy-Based Weighted Algorithm;IEEE Wireless Communications Letters;2023-12
4. A Blockchain-Based Method to Defend Against Massive SSDF Attacks in Cognitive Internet of Vehicles;IEEE Transactions on Vehicular Technology;2023
5. Gaussian Mixture Model Based Anomaly Detection for Defense Against Byzantine Attack in Cooperative Spectrum Sensing;IEEE Transactions on Cognitive Communications and Networking;2023
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3