Protecting Location Privacy in IoT Wireless Sensor Networks through Addresses Anonymity

Autor: Qiong Zhang, Kewang Zhang
Rok vydání: 2022
Předmět:
Zdroj: Security and Communication Networks. 2022:1-12
ISSN: 1939-0122
1939-0114
DOI: 10.1155/2022/2440313
Popis: Location privacy is very important for event-triggered type of Wireless Sensor Networks (WSNs) applications such as tracking and monitoring of wild animals. Most of the security schemes for WSNs are designed to provide protection for content privacy. Contextual privacy such as node identity anonymity has received much less attention. The adversary can fully explore such contextual information to disclose the location of critical components such as source nodes or base station. Most existing schemes provide location privacy at network layer. As no measures are taken to provide node identity anonymity at data link layer, the adversary can launch traffic analysis attacks to jeopardize location privacy. In this paper, a scheme named HASHA is proposed to defend against traffic analysis attacks through hashed one-time addresses. Hashed results of payload are used to create dynamic one-time MAC addresses between the communication pairs. Because of inevitable wireless frame errors, it is impossible for adversaries to track dynamic addresses. Therefore, HASHA can provide strong node identity anonymity, which makes traffic analysis attacks much more difficult and provides better location privacy. Simulations and analysis results show that HASHA can provide better location privacy with limited communication overheads, which is particularly suitable for resource-limited WSNs.
Databáze: OpenAIRE
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