Achieving k-anonymity in privacy-aware location-based services

By Ben Niu, Qinghua Li, Xiao-yan Zhu, Guohong Cao, Hui Li. IEEE Conference on Computer Communications, 2014

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PrivCheck: privacy-preserving check-in data publishing for personalized location based services (2016, methodology): “To achieve this goal, the user’s location data may be slightly altered or generalized using data obfuscation techniques such as cloaking region [15] and dummy location [30], in order to avoid revealing her real position.”
Internet of things security: A top-down survey (2018, background): “Particularly, in IoT applications, there are also some attempts to adopt k-anonymity models [95, 63, 65].”