Secure Data Assimilation of Cloud Sensor Networks

Quanyan Zhu, Zhiheng Xu

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Cloud computing technologies (CCTs) enable a large-scale sensor network (LSN) to outsource the computations of data assimilation to improve its performance. However, the cyber-physical nature of cloud-enabled LSNs (CE-LSNs) introduces new challenges. Outsourcing the computations to an untrusted cloud may expose the privacy of the sensing data. To address the security issues, this chapter proposes a security mechanism to achieve data confidentiality in the outsourcing process. We develop our mechanism by combining a conventional homomorphic encryption and a customized encryption scheme. We present theorems to characterize the correctness of the encryption and investigate the estimation performance and the security of the proposed method. We also analyze the impacts of the quantization errors on the estimation performance. Finally, we present numerical experiments to consolidate our analytical results.

Original languageEnglish (US)
Title of host publicationAdvances in Information Security
PublisherSpringer
Pages43-58
Number of pages16
DOIs
StatePublished - 2020

Publication series

NameAdvances in Information Security
Volume81
ISSN (Print)1568-2633

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications

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