Dimitriou Konstantinos, Roussaki Ioanna
School of Electrical and Computer Engineering, National Technical University of Athens and Greece, 15773 Athens, Greece.
Institute of Communication and Computer Systems, 10682 Athens, Greece.
Sensors (Basel). 2019 Jul 9;19(13):3022. doi: 10.3390/s19133022.
One of the most significant challenges in Internet of Things (IoT) environments is the protection of privacy. Failing to guarantee the privacy of sensitive data collected and shared over IoT infrastructures is a critical barrier that delays the wide penetration of IoT technologies in several user-centric application domains. Location information is the most common dynamic information monitored and lies among the most sensitive ones from a privacy perspective. This article introduces a novel mechanism that aims to protect the privacy of location information across Data Centric Sensor Networks (DCSNs) that monitor the location of mobile objects in IoT systems. The respective data dissemination protocols proposed enhance the security of DCSNs rendering them less vulnerable to intruders interested in obtaining the location information monitored. In this respect, a dynamic clustering algorithm is that clusters the DCSN nodes not only based on the network topology, but also considering the current location of the objects monitored. The proposed techniques do not focus on the prevention of attacks, but on enhancing the privacy of sensitive location information once IoT nodes have been compromised. They have been extensively assessed via series of experiments conducted over the IoT infrastructure of FIT IoT-LAB and the respective evaluation results indicate that the dynamic clustering algorithm proposed significantly outperforms existing solutions focusing on enhancing the privacy of location information in IoT.
物联网（IoT）环境中最重大的挑战之一是隐私保护。无法保证通过物联网基础设施收集和共享的敏感数据的隐私是一个关键障碍，这延缓了物联网技术在多个以用户为中心的应用领域的广泛渗透。位置信息是最常被监测的动态信息，从隐私角度来看也是最敏感的信息之一。本文介绍了一种新颖的机制，旨在保护跨数据中心传感器网络（DCSN）的位置信息隐私，该网络用于监测物联网系统中移动对象的位置。所提出的相应数据传播协议增强了DCSN的安全性，使其更不易受到获取所监测位置信息的入侵者的攻击。在这方面，一种动态聚类算法不仅基于网络拓扑对DCSN节点进行聚类，还考虑被监测对象的当前位置。所提出的技术并不侧重于预防攻击，而是在物联网节点被攻破后增强敏感位置信息的隐私性。通过在FIT IoT-LAB的物联网基础设施上进行的一系列实验，对这些技术进行了广泛评估，相应的评估结果表明，所提出的动态聚类算法明显优于现有的侧重于增强物联网中位置信息隐私的解决方案。
