Collusion-Resistant and Time-Aware Co-Verification for Edge Data Integrity

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Yao Zhao, Youyang Qu, Bo Li, Lu Zhao, Feifei Chen, Yong Xiang, Longxiang Gao

Published: 01 Jan 2025, Last Modified: 21 Jan 2026IEEE Transactions on Dependable and Secure ComputingEveryoneRevisionsCC BY-SA 4.0
Abstract: Mobile Edge Computing (MEC) has incentivized App vendors to outsource various services and applications to distributed edge nodes for low access latency. However, the data cached on these nodes is vulnerable to both intentional and accidental corruption, necessitating periodic audits of Edge Data Integrity (EDI). Existing solutions either rely on a “fully trustworthy” Third Party Auditor (TPA) or leverage blockchain to enhance trust. However, they overlook the security risks brought by the use of blockchain, particularly collusion attacks. Furthermore, while they employ a challenge-response mechanism to enhance efficiency by batch verification, they fail to account for the heterogeneity of edge nodes. To address these challenges, we propose $\mathtt {CTCV}$, a Collusion-resistant and Time-aware Collaborative Verification framework. $\mathtt {CTCV}$ aims to accommodate edge node heterogeneity while enabling public audits and batch verification without introducing additional security risks. Specifically, it incorporates blockchain to allow edge nodes to collaboratively verify EDI without trust dependencies, while mitigating collusion attacks through a carefully designed proof generation and verification approach. Considering the resource and state heterogeneity of edge nodes, $\mathtt {CTCV}$ employs a time-constrained challenge-response mechanism that sets a time threshold $\mathcal {T}$ between the verification request issuance and the integrity proof inspection to avoid excessive delays. The selection guideline of $\mathcal {T}$, along with the correctness, efficiency, and collusion resistance of $\mathtt {CTCV}$, are rigorously analyzed. Extensive experiments validate that $\mathtt {CTCV}$ is computationally and communicationally efficient compared to three baselines: EdgeWatch, EDI-S, and EDI-V. On average, given 10 edge nodes, $\mathtt {CTCV}$ outperforms EdgeWatch, EDI-S, and EDI-V with computation efficiency improvements of 7.9, 9.0, and 5.0 times, and communication efficiency improvement of 2063.0, 4.8, and 2.6 times, respectively.