articleFuture Generation Computer SystemsJan 11, 2025HYBRID OA

FedShufde: A privacy preserving framework of federated learning for edge-based smart UAV delivery system

AYAiting YaoSPShantanu PalGLGang LiXLXuejun LiZZZheng Zhang

Anhui University · Deakin University

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Abstract

In recent years, there has been a rapid increase in the integration of Internet of Things (IoT) systems into edge computing. This integration offers several advantages over traditional cloud computing, including lower latency and reduced network traffic. In addition, edge computing facilitates the protection of users’ sensitive data by processing it at the edge before transmitting it to the cloud using techniques such as federated learning (FL) and differential privacy (DP). However, these techniques have limitations, such as the risk of user information being obtained by attackers through the uploaded weights/model parameters in FL and the randomness of DP, which limits data availability. To address these…

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Topics & keywords

Topics
Keywords
  • Computer science
  • Enhanced Data Rates for GSM Evolution
  • Edge computing
  • Federated learning
  • Computer security
  • Human–computer interaction
  • Artificial intelligence
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