基于匿名轨迹和时间混淆技术的物联网用户位置隐私保护
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摘要
随着物联网的快速发展,用户位置隐私保护变得越来越重要。本文提出一种基于匿名轨迹和时间混淆技术的保护策略,旨在提高物联网用户位置隐私的保护级别。实验结果表明:采用匿名轨迹技术时,当r值越高,节点轨迹的隐藏程度就越深,可以长时间保护用户位置隐私;采用时间混淆技术时,整个节点轨迹都是模糊的,增加了攻击者的推测难度,用户位置隐私得到更强的保护。但是考虑到服务器性能,还需要结合控制查询方法,才能有效降低服务器的维护成本。
With the rapid development of the Internet of Things, user location privacy protection becomes more and more important. This paper proposes a protection strategy based on anonymous trajectory and time obfuscation technology aiming at improving the protection level of location privacy of Internet of Things users. The experimental results show that when using anonymous trajectory technology, the higher the r value, the deeper the hidden degree of the trajectory of the node and the user's location privacy can be protected for a long time. When using time obfuscation technology, the whole trajectory of the node is blurred, which increases the difficulty of the attacker's speculation, and the user's location privacy can be better protected. However, considering the performance of the server, we need to combine the control query method to effectively reduce the maintenance cost of the server.
With the rapid development of the Internet of Things, user location privacy protection becomes more and more important. This paper proposes a protection strategy based on anonymous trajectory and time obfuscation technology aiming at improving the protection level of location privacy of Internet of Things users. The experimental results show that when using anonymous trajectory technology, the higher the r value, the deeper the hidden degree of the trajectory of the node and the user's location privacy can be protected for a long time. When using time obfuscation technology, the whole trajectory of the node is blurred, which increases the difficulty of the attacker's speculation, and the user's location privacy can be better protected. However, considering the performance of the server, we need to combine the control query method to effectively reduce the maintenance cost of the server.
引文
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[10] Ullah I, Shah MA, Wahid A, et al. ESOT:a new privacy model for preserving location privacy in Internet of Things[J].Telecommunication systems:Modeling, Analysis, Design and Management, 2018,67(4):553-575
[2] González-Manzano L, de Fuentes JM, Pastrana S, et al. PAg IoT-Privacy-preserving Aggregation protocol for Internet of Things[J]. Journal of network and computer applications, 2016,71(6):59-71
[3] Alrawais A, Alhothaily A, Hu CQ, et al. Fog Computing for the Internet of Things:Security and Privacy Issues[J].IEEE internet computing, 2017,21(2):34-42
[4] Shafiq SI, Szczerbicki E, Sanin C. Manufacturing Data Analysis in Internet of Things/Internet of Data(Io T/Io D)Scenario[J].Cybernetics and Systems, 2018,49(5-6):280-295
[5] Arias O, Jacob W, Hoang K, et al. Privacy and Security in Internet of Things and Wearable Devices[J]. IEEE transactions on multi-scale computing systems, 2015,1(2):99-109
[6] Perera C, Ranjan R, Wang LZ, et al. Big Data Privacy in the Internet of Things Era[J]. ITprofessional, 2014,17(3):32-39
[7] Weber RH. Internet of things:Privacy issues revisited[J]. Computer law&security report,2015,31(5):618-627
[8] Alaba FA, Othman M, Hashem I AT, et al. Internet of Things security:A survey[J]. Journal of network and computer applications, 2017,88(4):10-28
[9] Sun M, Tay WP, He X. Toward Information Privacy for the Internet of Things:A Nonparametric Learning Approach[J]. IEEE Transactions on Signal Processing, 2018,66(7):1734-1747
[10] Ullah I, Shah MA, Wahid A, et al. ESOT:a new privacy model for preserving location privacy in Internet of Things[J].Telecommunication systems:Modeling, Analysis, Design and Management, 2018,67(4):553-575