Packet Padding for Improving Privacy in Consumer IoT
Packet Padding for Improving Privacy in Consumer IoT
复制标题
用于改善消费者物联网隐私的数据包填充
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Divanilson R. Campelo
中科院分区：
文献类型：
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作者：
Antônio J. Pinheiro;Jeandro M. Bezerra;Divanilson R. Campelo
侧通道信息的流量分析代表了消费者IoT隐私的主要关注点，因为它可能导致用户数据和行为泄漏。在本文中，我们提出了一种基于轻质填充的机制，以使一种类型的侧通道信息（数据包长度）混淆，以增强用户隐私。该机制的原型与五个不同的机器学习分类器一起在虚拟机中实现，该分类器用于通过数据包长度模式来识别IoT设备。结果表明，数据包填充机制能够在至少75％的情况下降低分类器的准确性，从而增强了物联网通信的隐私。此外，使用延迟，抖动，吞吐量和数据包丢失来量化机制对IoT设备通信性能的影响。结果表明，通过提议的机制产生的通信开销将其保持在最低限度。
Traffic analysis of side-channel information represents a major concern in consumer IoT privacy, since it can lead to a leakage of user data and behavior. In this paper, we propose a lightweight padding-based mechanism to obfuscate one type of side-channel information, the packet length, in order to enhance user privacy. A prototype of the mechanism is implemented in a virtual machine along with five different machine learning classifiers, which are used to identify IoT devices by means of packet length patterns. Results show that the packet padding mechanism is able to reduce the accuracy of the classifiers in at least 75%, thus enhancing the privacy of the IoT communication. Additionally, the delay, jitter, throughput and packet loss are used to quantify the impact of the mechanism on the communication performance of the IoT devices. It is shown that the communication overhead generated the by proposed mechanism was kept to a minimum.