Literature Database Entry

chen2021privacy-preserving

Shuzhen Chen, Youming Tao, Dongxiao Yu, Feng Li, Bei Gong and Xiuzhen Cheng, "Privacy-Preserving Collaborative Learning for Multiarmed Bandits in IoT," IEEE Internet of Things Journal, vol. 8 (5), pp. 3276–3286, March 2021.

Abstract

This article studies privacy-preserving collaborative learning in decentralized Internet-of-Things (IoT) networks, where the agents exchange information constantly to improve the learnability, and meanwhile make the privacy of agents protected during communications. However, the harsh constraints in IoT make executing collaborative learning much more difficult than well-connected systems composed by servers with strong computation power, due to the weak capacity of devices, limited bandwidth for exchanging information, the asynchronous communication environment, and the necessity of privacy preserving. We show that even if with the harsh constraints in IoT, it still can devise efficient privacy-preserving collaborative learning algorithms, by proposing the first known decentralized collaborative learning algorithm for the fundamental multiarmed bandits problem under the framework of local differential privacy. Rigorous analysis shows that the proposed learning algorithm can make every agent learn the best arm with a high probability and keep the privacy preserved meanwhile. Extensive experiments illustrate that our learning algorithm performs well in real settings.

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Shuzhen Chen
Youming Tao
Dongxiao Yu
Feng Li
Bei Gong
Xiuzhen Cheng

BibTeX reference

@article{chen2021privacy-preserving,
    author = {Chen, Shuzhen and Tao, Youming and Yu, Dongxiao and Li, Feng and Gong, Bei and Cheng, Xiuzhen},
    doi = {10.1109/jiot.2020.3015986},
    title = {{Privacy-Preserving Collaborative Learning for Multiarmed Bandits in IoT}},
    pages = {3276--3286},
    journal = {IEEE Internet of Things Journal},
    issn = {2327-4662},
    publisher = {IEEE},
    month = {3},
    number = {5},
    volume = {8},
    year = {2021},
   }
   
   

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Last modified: 2024-05-20