基于累积可疑等级的协同频谱感知SSDF攻击排除方案

Siyang Liu, Quan Liu, Jun Gao, Jianxin Guan
{"title":"基于累积可疑等级的协同频谱感知SSDF攻击排除方案","authors":"Siyang Liu, Quan Liu, Jun Gao, Jianxin Guan","doi":"10.1109/CYBER.2011.6011801","DOIUrl":null,"url":null,"abstract":"Cooperative spectrum sensing (CSS) is one of the vital mechanisms of cognitive radio (CR), however, its security area has attracted very little attention, which is vulnerable to the attacks of malicious secondary users. To counter the spectrum sensing data falsification (SSDF) attacks, an accumulated suspicious level-based algorithm was proposed. Based on all secondary users' reporting histories, it calculates the accumulated suspicious level and distinguishes honest users and attackers. Then, only the honest secondary users will be incorporated in decision combination at the fusion centre, which improves the robustness of CSS against SSDF attacks. Simulation results illustrated the effectiveness of the proposed scheme. Unlike other existing schemes, the algorithm does not assume any a priori information about the strategy of attackers and can effectively detect the intelligent attackers.","PeriodicalId":131682,"journal":{"name":"2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Attacker-exclusion scheme for cooperative spectrum sensing against SSDF attacks based on accumulated suspicious level\",\"authors\":\"Siyang Liu, Quan Liu, Jun Gao, Jianxin Guan\",\"doi\":\"10.1109/CYBER.2011.6011801\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cooperative spectrum sensing (CSS) is one of the vital mechanisms of cognitive radio (CR), however, its security area has attracted very little attention, which is vulnerable to the attacks of malicious secondary users. To counter the spectrum sensing data falsification (SSDF) attacks, an accumulated suspicious level-based algorithm was proposed. Based on all secondary users' reporting histories, it calculates the accumulated suspicious level and distinguishes honest users and attackers. Then, only the honest secondary users will be incorporated in decision combination at the fusion centre, which improves the robustness of CSS against SSDF attacks. Simulation results illustrated the effectiveness of the proposed scheme. Unlike other existing schemes, the algorithm does not assume any a priori information about the strategy of attackers and can effectively detect the intelligent attackers.\",\"PeriodicalId\":131682,\"journal\":{\"name\":\"2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CYBER.2011.6011801\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CYBER.2011.6011801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

协同频谱感知(CSS)是认知无线电(CR)的重要机制之一,但其安全领域受到的关注很少,容易受到恶意二次用户的攻击。针对频谱感知数据伪造(SSDF)攻击,提出了一种基于累积可疑等级的算法。根据所有二级用户的报告历史,计算可疑级别的累积,区分诚实用户和攻击者。然后,只有诚实的次要用户才会被纳入融合中心的决策组合,从而提高CSS对SSDF攻击的鲁棒性。仿真结果表明了该方案的有效性。与现有方案不同的是,该算法不假设攻击者策略的先验信息,能够有效地检测出智能攻击者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Attacker-exclusion scheme for cooperative spectrum sensing against SSDF attacks based on accumulated suspicious level
Cooperative spectrum sensing (CSS) is one of the vital mechanisms of cognitive radio (CR), however, its security area has attracted very little attention, which is vulnerable to the attacks of malicious secondary users. To counter the spectrum sensing data falsification (SSDF) attacks, an accumulated suspicious level-based algorithm was proposed. Based on all secondary users' reporting histories, it calculates the accumulated suspicious level and distinguishes honest users and attackers. Then, only the honest secondary users will be incorporated in decision combination at the fusion centre, which improves the robustness of CSS against SSDF attacks. Simulation results illustrated the effectiveness of the proposed scheme. Unlike other existing schemes, the algorithm does not assume any a priori information about the strategy of attackers and can effectively detect the intelligent attackers.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信