文献类型：期刊文献

英文题名：Optimal privacy preservation strategies with signaling Q-learning for edge-computing-based IoT resource grant systems

作者：Shen, Shigen[1];Wu, Xiaoping[1];Sun, Panjun[2];Zhou, Haiping[2];Wu, Zongda[2];Yu, Shui[3]

机构：[1]Huzhou Univ, Sch Informat Engn, Huzhou 313000, Peoples R China;[2]Shaoxing Univ, Dept Comp Sci & Engn, Shaoxing 312000, Peoples R China;[3]Univ Technol Sydney, Sch Comp Sci, Ultimo, NSW, Australia

年份：2023

卷号：225

外文期刊名：EXPERT SYSTEMS WITH APPLICATIONS

收录：SCI-EXPANDED(收录号：WOS:000983799200001)、、EI(收录号：20231713951849)、Scopus(收录号：2-s2.0-85153051602)、WOS

基金：Acknowledgements This work was supported by Humanities and Social Sciences Plan- ning Foundation of Ministry of Education of China under Grant No. 22YJAZH090, and Zhejiang Provincial Natural Science Foundation of China under Grant No. LZ22F020002.

语种：英文

外文关键词：Internet of Things; Edge computing; Privacy preservation; Signaling game; Signaling Q -learning

外文摘要：Data privacy leakage can be severe when a malicious Internet of Things (IoT) node sends requests to gather private data from an edge-computing-based IoT cloud storage system across the edge nodes. To solve this problem, a privacy-preservation signaling game for edge-computing-based IoT networks is proposed to characterize the interactions between an IoT node and its corresponding edge node when managing an IoT resourcegrant system. Optimal privacy preservation strategies for edge nodes are then theoretically derived. A signaling Q-learning algorithm is then designed to address the problem of achieving convergent equilibrium and game parameters from a practical perspective. The theoretical results are validated using simulations that focus on two statistical points (i.e., the optimal probability of an IoT node requesting maliciously and the posterior probability of an IoT node being malicious). By comparing the proposed signaling Q-learning algorithm with the greedy algorithm benchmark, the proposed algorithm is shown to more effectively decrease the optimal probability of an IoT node sending malicious requests. Thus, privacy preservation for edge-computing-based IoT cloud storage systems can be strengthened.