With rapid advancements in handheld mobile devices (HMDs), striking a balance between storage and data security is crucial. Cloud storage has attracted great attention of users for its convenience and availability. However, data integrity becomes challenging once data is uploaded to the cloud, as physical control is lost. In this paper, we propose an efficient identity-based dynamic cloud storage data integrity auditing protocol for HMDs. Our protocol simplifies certificate management and avoids the use of Map to Point (MtP) operation during private key extraction, resulting in a 50% improvement in private key verification efficiency compared to other protocols. We optimize tag generation computation, enhancing efficiency for computation-constrained users. Furthermore, our protocol supports incremental updates for dynamic data operations. We provide detailed system and security models, demonstrating the protocol’s security in ensuring data integrity and auditing soundness. Performance comparisons reveal the computation cost advantages of our protocol, making it ideal for application in cloud-based HMDs.

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Efficient Identity-Based Dynamic Cloud Storage Data Integrity Auditing with Incremental Updates for Handheld Mobile Devices

  • Yichi Huang,
  • Futai Zhang,
  • Wenjie Yang,
  • Shaojun Yang

摘要

With rapid advancements in handheld mobile devices (HMDs), striking a balance between storage and data security is crucial. Cloud storage has attracted great attention of users for its convenience and availability. However, data integrity becomes challenging once data is uploaded to the cloud, as physical control is lost. In this paper, we propose an efficient identity-based dynamic cloud storage data integrity auditing protocol for HMDs. Our protocol simplifies certificate management and avoids the use of Map to Point (MtP) operation during private key extraction, resulting in a 50% improvement in private key verification efficiency compared to other protocols. We optimize tag generation computation, enhancing efficiency for computation-constrained users. Furthermore, our protocol supports incremental updates for dynamic data operations. We provide detailed system and security models, demonstrating the protocol’s security in ensuring data integrity and auditing soundness. Performance comparisons reveal the computation cost advantages of our protocol, making it ideal for application in cloud-based HMDs.