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Trajectory Privacy Preservation in Mobile Wireless Sensor Networks

机译:移动无线传感器网络中的轨迹隐私保护

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摘要

In recent years, there has been an enormous growth of location-aware devices, such as GPS embedded cell phones, mobile sensors and radio-frequency identification tags. The age of combining sensing, processing and communication in one device, gives rise to a vast number of applications leading to endless possibilities and a realization of mobile Wireless Sensor Network (mWSN) applications. As computing, sensing and communication become more ubiquitous, trajectory privacy becomes a critical piece of information and an important factor for commercial success. While on the move, sensor nodes continuously transmit data streams of sensed values and spatiotemporal information, known as ``trajectory informationu22. If adversaries can intercept this information, they can monitor the trajectory path and capture the location of the source node.This research stems from the recognition that the wide applicability of mWSNs will remain elusive unless a trajectory privacy preservation mechanism is developed. The outcome seeks to lay a firm foundation in the field of trajectory privacy preservation in mWSNs against external and internal trajectory privacy attacks. First, to prevent external attacks, we particularly investigated a context-based trajectory privacy-aware routing protocol to prevent the eavesdropping attack. Traditional shortest-path oriented routing algorithms give adversaries the possibility to locate the target node in a certain area. We designed the novel privacy-aware routing phase and utilized the trajectory dissimilarity between mobile nodes to mislead adversaries about the location where the message started its journey. Second, to detect internal attacks, we developed a software-based attestation solution to detect compromised nodes. We created the dynamic attestation node chain among neighboring nodes to examine the memory checksum of suspicious nodes. The computation time for memory traversal had been improved compared to the previous work. Finally, we revisited the trust issue in trajectory privacy preservation mechanism designs. We used Bayesian game theory to model and analyze cooperative, selfish and malicious nodesu27 behaviors in trajectory privacy preservation activities.
机译:近年来,诸如GPS嵌入式手机,移动传感器和射频识别标签之类的位置感知设备有了巨大的增长。将感测,处理和通信结合在一个设备中的时代出现了众多的应用程序,从而带来了无限的可能性,并实现了移动无线传感器网络(mWSN)应用程序。随着计算,传感和通信的普及,轨迹的隐私性成为至关重要的信息,也是商业成功的重要因素。在移动过程中,传感器节点连续传输感测值和时空信息的数据流,称为``轨迹信息''。如果对手能够拦截这些信息,他们就可以监视轨迹路径并捕获源节点的位置。本研究基于这样的认识,即除非开发出轨迹隐私保护机制,否则mWSN的广泛应用仍将是遥不可及的。该结果旨在为mWSN中针对外部和内部轨迹隐私攻击的轨迹隐私保护领域奠定坚实的基础。首先,为了防止外部攻击,我们特别研究了一种基于上下文的轨迹隐私感知路由协议,以防止窃听攻击。传统的面向最短路径的路由算法使对手有可能在特定区域内定位目标节点。我们设计了新颖的隐私感知路由阶段,并利用移动节点之间的轨迹差异来误导对手有关消息开始传播的位置的信息。其次,为了检测内部攻击,我们开发了基于软件的证明解决方案来检测受感染的节点。我们在相邻节点之间创建了动态证明节点链,以检查可疑节点的内存校验和。与以前的工作相比,内存遍历的计算时间得到了改善。最后,我们重新探讨了轨迹隐私保护机制设计中的信任问题。我们使用贝叶斯博弈论对轨迹隐私保护活动中的合作,自私和恶意节点行为进行建模和分析。

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    Jin Xinyu;

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