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<p>With the rapid development of Industrial Internet of Things (IIoT) and explosive growth of industrial data, industrial enterprises confront serious challenge in data management. Cloud computing could be integrated into IIoT to provide powerful data computing and storage services. However, the security and privacy issues of outsourced industrial data have been extremely concerned. To ensure industrial data confidentiality and integrity, protect the identity privacy of each terminal user, a lightweight batch tamper proof detection mechanism for anonymous outsourced data in cloud-assisted Industrial Internet of Things is devised. The mechanism resorts to a third-party auditor (TPA) to publicly detect the integrity of batch data files from different terminal users with nearly constant computational costs, independent of the number of data files. The mechanism achieves conditional identity anonymity, enables to track and revoke the real identity of each malicious user in case of misbehaviors. The security analysis and performance evaluation are conducted to demonstrate the lightweight computation advantages of the mechanism in the secure deployment of cloud-assisted IIoT, which is specifically suitable for TPA with constrained resources in terminal devices or mobile wireless communication systems.</p>

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Lightweight batch tamper proof detection for anonymous outsourced data in cloud-assisted industrial internet of things

  • 期刊论文

  • 发表日期：

    2025年7月5日

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  • Bingyun Liu,
  • Xiaojun Zhang,
  • Chong Zhang,
  • Lei Li,
  • Jingting Xue

摘要

With the rapid development of Industrial Internet of Things (IIoT) and explosive growth of industrial data, industrial enterprises confront serious challenge in data management. Cloud computing could be integrated into IIoT to provide powerful data computing and storage services. However, the security and privacy issues of outsourced industrial data have been extremely concerned. To ensure industrial data confidentiality and integrity, protect the identity privacy of each terminal user, a lightweight batch tamper proof detection mechanism for anonymous outsourced data in cloud-assisted Industrial Internet of Things is devised. The mechanism resorts to a third-party auditor (TPA) to publicly detect the integrity of batch data files from different terminal users with nearly constant computational costs, independent of the number of data files. The mechanism achieves conditional identity anonymity, enables to track and revoke the real identity of each malicious user in case of misbehaviors. The security analysis and performance evaluation are conducted to demonstrate the lightweight computation advantages of the mechanism in the secure deployment of cloud-assisted IIoT, which is specifically suitable for TPA with constrained resources in terminal devices or mobile wireless communication systems.