DBF: A general framework for anomaly detection in RFID systems
DBF: A general framework for anomaly detection in RFID systems
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DOI：
10.1109/infocom.2017.8056986
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发表时间：
2017-05
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影响因子：
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通讯作者：
Min Chen;Jia Liu;Shigang Chen;Yan Qiao;Yuanqing Zheng
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文献类型：
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作者：
Min Chen;Jia Liu;Shigang Chen;Yan Qiao;Yuanqing Zheng
RFID技术正在进入许多应用领域，包括库存管理、供应链、产品跟踪、运输、物流等。一个重要的应用是自动检测RFID系统中的异常，如丢失标签、未知标签或由于盗窃、管理错误或有针对性的攻击而克隆的标签。现有的解决方案都是为检测某种类型的RFID异常而设计的，但是缺乏用于检测不同类型的异常的通用功能。本文试图提出一种通用的RFID系统异常检测框架，从而降低阅读器和标签实现不同异常检测协议的复杂性。提出了差分布隆过滤器(DBF)的概念，它将物理层的信号数据转换为分段的布隆过滤器，对异常标签的ID进行编码。作为一个案例研究，我们提出了一种构建DBF的协议，用于高效地识别所有缺失的标签。为了验证协议的有效性，我们实现了一个基于USRP和WISP标签的遗漏标签识别原型，并使用大规模的仿真对其进行了性能评估。结果表明，与现有最好的工作相比，我们的解决方案可以显著提高时间效率。
RFID technologies are making their way into numerous applications, including inventory management, supply chain, product tracking, transportation, logistics, etc. One important application is to automatically detect anomalies in RFID systems, such as missing tags, unknown tags, or cloned tags due to theft, management error, or targeted attacks. Existing solutions are all designed to detect a certain type of RFID anomalies, but lack a general functionality for detecting different types of anomalies. This paper attempts to propose a general framework for anomaly detection in RFID systems, thereby reducing the complexity for readers and tags to implement different anomaly-detection protocols. We introduce a new concept of differential Bloom filter (DBF), which turns physical-layer signal data into a segmented Bloom filter that encodes the IDs of abnormal tags. As a case study, we propose a protocol that builds DBF for identifying all missing tags in an efficient way. We implement a prototype for missing-tag identification using USRP and WISP tags to verify the effectiveness our protocol, and use large-scale simulations for performance evaluation. The results show that our solution can significantly improve time efficiency, when comparing with the best existing work.