首页> 外文OA文献 >Detect and identify blocker tags in tree-based RFID systems
【2h】

Detect and identify blocker tags in tree-based RFID systems

机译:在基于树的RFID系统中检测和识别阻止器标签

摘要

Blocker tags are initially introduced to protect regular tags in certain ID ranges, called blocking ranges, from unwanted scanning in RFID systems. But if misused, blocker tags can cause blocking attacks that corrupt the communication between interfered regular tags and readers. Previous approaches can only detect blocking behavior. However, they cannot distinguish malicious blocking from legitimate blocking that can be perfectly allowed to protect customer's privacy. To solve the problem, we carry out the first attempt in the paper to detect real blocking attacks by identifying malicious blocking ranges from authorized ones in a system. We present two pioneer probe-based protocols that can accurately identify malicious blocking ranges in popular tree-based RFID systems, and get rid of their impact before performing RFID applications. We validate the efficacy of the two protocols through theoretical analysis and simulation experiments. The results show that our protocols can identify blocking ranges very fast even when the blocker tag percentage is very low, for example, dozens of blocker tags among tens of thousands of regular tags. Our protocols deliver also a faster blocker tag detection than previous detection methods; our best protocol reduces detection time by over 90% compared with the state-of-the-art detection method.
机译:最初引入阻止器标签是为了保护某些ID范围内的常规标签(称为阻止范围)免受RFID系统中不必要的扫描。但是,如果误用了标签,拦截器标签可能会导致拦截攻击,从而破坏受干扰的常规标签和读取器之间的通信。先前的方法只能检测阻塞行为。但是,他们无法将恶意阻止与合法阻止区分开来,可以完全允许保护用户隐私。为了解决这个问题,我们进行了本文中的第一次尝试,通过从系统中授权的恶意程序中识别出恶意的拦截范围来检测实际的拦截攻击。我们提出了两种基于探针的先锋协议,它们可以准确地识别流行的基于树的RFID系统中的恶意阻止范围,并在执行RFID应用之前消除它们的影响。我们通过理论分析和模拟实验验证了这两种协议的有效性。结果表明,即使在拦截器标签百分比非常低的情况下,例如在成千上万的常规标签中有数十个拦截器标签,我们的协议也可以非常快速地识别拦截范围。与以前的检测方法相比,我们的协议还提供了更快的阻止者标签检测;与最新的检测方法相比,我们最好的协议可将检测时间减少90%以上。

著录项

  • 作者

    Wang F; Xiao B; Bu K; Su J;

  • 作者单位
  • 年度 2013
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号