Analysis of Wireless Signature Feature Sets for Commercial IoT Devices : Invited Presentation

Asia Mason, Michel Reece, Gian Claude, Willie L. Thompson, K. Kornegay
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引用次数: 1

Abstract

Advances in technology have led to an increase the number and type of electronic devices interconnected through the internet, or Internet of Things (IoT) devices. These devices are available commercially and are often used for applications in home environments, office buildings, medical facilities, and others. A common protocol used in IoT devices is the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 protocol. The vulnerabilities of the standard have led to numerous attacks on devices that follow this protocol. RF fingerprinting is a technique used to authenticate and verify devices in an environment to determine if they are either authorized or rogue to add a level of security at the physical layer. The fingerprints are comprised of statistical features, such as variance, skewness, and kurtosis, extracted from instantaneous RF signal characteristics. Previous RF fingerprinting work obtained features from generic ZigBee modules. This work aims to examine signal features of commercial IoT devices that adhere to the ZigBee protocol. The analysis will highlight correlations, if any, and differences between device vendor and IoT device type.
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商用物联网设备无线签名特征集分析:特邀报告
技术的进步导致通过互联网或物联网(IoT)设备互联的电子设备的数量和类型增加。这些设备在商业上是可用的,通常用于家庭环境、办公楼、医疗设施和其他应用。物联网设备中使用的常用协议是电气和电子工程师协会(IEEE) 802.15.4协议。该标准的漏洞导致了对遵循该协议的设备的大量攻击。射频指纹识别是一种用于验证和验证环境中的设备的技术,以确定它们是经过授权的还是非法的,从而在物理层增加一个安全级别。指纹由统计特征组成,如方差、偏度和峰度,从射频信号的瞬时特征提取。以前的射频指纹识别工作获得了通用ZigBee模块的特征。这项工作旨在研究遵循ZigBee协议的商用物联网设备的信号特征。分析将强调设备供应商和物联网设备类型之间的相关性(如果有的话)和差异。
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