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In addressing the challenges of privacy protection and the lack of personalization in data sharing within the Power Internet of Things (PIoT), this paper proposes a lightweight retrieval method based on attribute differentiation. We design a personalized retrieval model that incorporates attribute distinction and introduce an edge-cloud collaborative lightweight search method along with a hybrid lightweight search framework. The proposed personalized retrieval approach generates data replicas tailored to the attributes of electricity users, thereby reducing the number of replicas and alleviating computational burdens. Simulation results demonstrate that this solution achieves lower computational overhead and higher search efficiency.

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Attribute Differentiation Based Lightweight Encrypted Search Method Towards Power Internet of Things

  • 会议论文

  • 发表日期：

    2025年

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  • Hai Chen,
  • Hongbo Ma,
  • Jie Liu,
  • Yingqi Zhang,
  • Wenfeng Xue,
  • Yue Wang,
  • Yingxue Sun,
  • Mu Chen

摘要

In addressing the challenges of privacy protection and the lack of personalization in data sharing within the Power Internet of Things (PIoT), this paper proposes a lightweight retrieval method based on attribute differentiation. We design a personalized retrieval model that incorporates attribute distinction and introduce an edge-cloud collaborative lightweight search method along with a hybrid lightweight search framework. The proposed personalized retrieval approach generates data replicas tailored to the attributes of electricity users, thereby reducing the number of replicas and alleviating computational burdens. Simulation results demonstrate that this solution achieves lower computational overhead and higher search efficiency.