{"title":"检测对比例公平调度程序的错误报告攻击","authors":"J. F. Schmidt, Roberto López-Valcarce","doi":"10.1109/WIFS.2014.7084310","DOIUrl":null,"url":null,"abstract":"The Proportional Fair Scheduler (PFS) has become a popular channel-aware resource allocation method in wireless networks, as it effectively exploits multiuser diversity while providing fairness to users. PFS decisions on which mobile station (MS) to schedule next are based on Channel Quality Indicator (CQI) values. Since CQI values are reported by the MSs to the scheduler, network performance can be severely degraded if some malicious MSs report forged information. Previous approaches to this security issue are based either on modifying PFS, which may be undesirable in some contexts, or authenticating CQI reports by periodic transmission of challenges, which increases overhead. Instead, we propose to detect misreporting attackers, based on the time correlation features of the wireless channel. Our approach does not require scheduler modification, and it does not increase overhead. Simulation results under realistic settings are provided to show the effectiveness of the proposed test.","PeriodicalId":220523,"journal":{"name":"2014 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detecting misreporting attacks to the proportional fair scheduler\",\"authors\":\"J. F. Schmidt, Roberto López-Valcarce\",\"doi\":\"10.1109/WIFS.2014.7084310\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Proportional Fair Scheduler (PFS) has become a popular channel-aware resource allocation method in wireless networks, as it effectively exploits multiuser diversity while providing fairness to users. PFS decisions on which mobile station (MS) to schedule next are based on Channel Quality Indicator (CQI) values. Since CQI values are reported by the MSs to the scheduler, network performance can be severely degraded if some malicious MSs report forged information. Previous approaches to this security issue are based either on modifying PFS, which may be undesirable in some contexts, or authenticating CQI reports by periodic transmission of challenges, which increases overhead. Instead, we propose to detect misreporting attackers, based on the time correlation features of the wireless channel. Our approach does not require scheduler modification, and it does not increase overhead. Simulation results under realistic settings are provided to show the effectiveness of the proposed test.\",\"PeriodicalId\":220523,\"journal\":{\"name\":\"2014 IEEE International Workshop on Information Forensics and Security (WIFS)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Workshop on Information Forensics and Security (WIFS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WIFS.2014.7084310\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Workshop on Information Forensics and Security (WIFS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIFS.2014.7084310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detecting misreporting attacks to the proportional fair scheduler
The Proportional Fair Scheduler (PFS) has become a popular channel-aware resource allocation method in wireless networks, as it effectively exploits multiuser diversity while providing fairness to users. PFS decisions on which mobile station (MS) to schedule next are based on Channel Quality Indicator (CQI) values. Since CQI values are reported by the MSs to the scheduler, network performance can be severely degraded if some malicious MSs report forged information. Previous approaches to this security issue are based either on modifying PFS, which may be undesirable in some contexts, or authenticating CQI reports by periodic transmission of challenges, which increases overhead. Instead, we propose to detect misreporting attackers, based on the time correlation features of the wireless channel. Our approach does not require scheduler modification, and it does not increase overhead. Simulation results under realistic settings are provided to show the effectiveness of the proposed test.