A passive means based privacy protection method for the perceptual layer of IoTs
A passive means based privacy protection method for the perceptual layer of IoTs
复制标题
一种基于被动手段的物联网感知层隐私保护方法
DOI：
10.1145/3011141.3011153
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Daoping Huang
中科院分区：
文献类型：
--
作者：
Xiaoyu Li;O. Yoshie;Daoping Huang
物联网（IoT）中的隐私保护在过去十年中一直是广泛研究的主题。物联网感知层由于硬件资源的限制，隐私泄露最为严重。数据加密和匿名化是保护物联网感知层隐私信息的最常用方法。然而，这些努力是无效的，以避免隐私泄露，如果通信环境中存在未知的无线节点，可能是恶意设备。因此，在本文中，我们推导出一种创新的和被动的方法，称为水平层次切片（HHS）的方法来检测未知的无线设备，可能会导致负面的隐私手段的存在。利用PAM算法对HHS曲线进行聚类，分析通信环境中是否存在未知无线设备。本文采用链路质量指标数据作为网络参数。仿真结果表明了它们在隐私保护方面的有效性。
Privacy protection in Internet of Things (IoTs) has long been the topic of extensive research in the last decade. The perceptual layer of IoTs suffers the most significant privacy disclosing because of the limitation of hardware resources. Data encryption and anonymization are the most common methods to protect private information for the perceptual layer of IoTs. However, these efforts are ineffective to avoid privacy disclosure if the communication environment exists unknown wireless nodes which could be malicious devices. Therefore, in this paper we derive an innovative and passive method called Horizontal Hierarchy Slicing (HHS) method to detect the existence of unknown wireless devices which could result negative means to the privacy. PAM algorithm is used to cluster the HHS curves and analyze whether unknown wireless devices exist in the communicating environment. Link Quality Indicator data are utilized as the network parameters in this paper. The simulation results show their effectiveness in privacy protection.