Utilizing RF Interference to Enable Private Estimation in RFID Systems

Lei Yang, Jinsong Han, Yong Qi, Cheng Wang, Zhuo Li, Qingsong Yao, Ying Chen, Xiao Zhong
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引用次数: 1

Abstract

Counting or estimating the number of tags is crucial for RFID system. Researchers have proposed several fast cardinality estimation schemes to estimate the quantity of a batch of tags within a short time frame. Existing estimation schemes scarcely consider the privacy issue. Without effective protection, the adversary can utilize the responding signals to estimate the number of tags as accurate as the valid reader. To address this issue, we propose a novel privacy-preserving estimation scheme, termed as MEAS, which provides an active RF countermeasure against the estimation from invalid readers. MEAS comprises of two components, an Estimation Interference Device (EID) and two well-designed Interference Blanking Estimators (IBE). EID is deployed with the tags to actively generate interfering signals, which introduce sufficiently large estimation errors to invalid or malicious readers. Using a secret interference factor shared with EID, a valid reader can perform accurate estimation via two IBEs. Our theoretical analysis and simulation results show the effectiveness of MEAS. Meanwhile, MEAS can also maintain a high estimation accuracy using IBEs.
利用射频干扰实现RFID系统的私有估计
标签数量的计算或估计对RFID系统至关重要。为了在短时间内估计一批标签的数量,研究人员提出了几种快速基数估计方案。现有的估计方案很少考虑隐私问题。如果没有有效的保护,攻击者可以利用响应信号来估计标签的数量,与有效的读取器一样准确。为了解决这个问题,我们提出了一种新的隐私保护估计方案,称为MEAS,它提供了一种主动的射频对抗来自无效读取器的估计。MEAS由两个部分组成,一个估计干扰装置(EID)和两个精心设计的干扰消隐估计器(IBE)。随着标签的部署,EID会主动产生干扰信号,这会给无效或恶意的读取器带来足够大的估计误差。使用与EID共享的秘密干扰因子,有效的读取器可以通过两个ibe进行准确的估计。理论分析和仿真结果表明了MEAS的有效性。同时,MEAS还可以使用ibe保持较高的估计精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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