Local differential privacy is a promising privacy-preserving model for statistical aggregation of user data that prevents user privacy leakage from the data aggregator. This paper focuses on the problem of estimating the distribution of discrete user values with Local differential privacy. We review and present a comparative analysis on the performance of the existing discrete distribution estimation algorithms in terms of their accuracy on benchmark datasets. Our evaluation benchmarks include real-world and synthetic datasets of categorical individual values with the number of individuals from hundreds to millions and the domain size up to a few hundreds of values. The experimental results show that the Basic RAPPOR algorithm generally performs best for the benchmark datasets in the high privacy regime while the k-RR algorithm often gives the best estimation in the low privacy regime. In the medium privacy regime, the performance of the k-RR, the k-subset, and the HR algorithms are fairly competitive with each other and generally better than the performance of the Basic RAPPOR and the CMS algorithms.
|Title of host publication||2021 IEEE International conference on pervasive computing and communications workshops and other affiliated events, (PerCom Workshops 2021)|
|Publisher||IEEE, Institute of Electrical and Electronics Engineers|
|Number of pages||6|
|Publication status||E-pub ahead of print - 25 May 2021|
|Event||The 19th International Conference on Pervasive Computing and Communications 2021: PerCom 2021 - Virtual, Germany|
Duration: 22 Mar 2021 → 26 Mar 2021
https://drive.google.com/file/d/1nLj_2g3UsnjgIS-zUJXxi70K8VbkH3HO/view (SPT-IoT 2021: The Fifth Workshop on Security, Privacy and Trust in the Internet of Things (part of PerCom 2021) program)
https://web.archive.org/web/20220307181306/http://percom.uta.edu/ (Conference website)
|Name||2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021|
|Conference||The 19th International Conference on Pervasive Computing and Communications 2021|
|Period||22/03/21 → 26/03/21|
|Other||IEEE PerCom is the premier conference for presenting scholarly research in pervasive computing and communications. Advances in this field are leading to innovative platforms, protocols, systems, and applications for always-on, always-connected services.|
In 2021, PerCom will visit Kassel, situated at the geographic center of Germany and a dynamic industrial and cultural city. It is known for its UNESCO World Heritage site 'Bergpark Wilhemshöhe' and famous for a leading exhibition of contemporary art 'documenta'.
In the light of the international situation of the CoVID-19 pandemic, the PerCom General Chairs and Steering Committee have decided that PerCom 2021 will be virtual (synchronous zoom meeting).