Blockchain-based verification framework for data integrity in edge-cloud storage

Abstract With the popularity of the Internet of Things (IoT), data integrity verification in the edge cloud storage attracts attentions from many researchers. Due to the over dependence of the Third Party Auditor (TPA) and the dynamical nature of the IoT data, the traditional data integrity verification framework for cloud storage can hardly work. To satisfy the characteristics of the IoT and avoid the over dependence of the TPA, we propose a blockchain-based framework without TPA for data integrity verification in a decentralized edge-cloud storage (ECS) scenario in this paper. In our framework, we employ the Merkle tree with random challenging numbers for data integrity verification and analyze different Merkle tree structures to optimize the system performance. To solve the problem of limited resources and high real-time requirements, we further propose sampling verification and develop rational sampling strategies to make sampling verification more effective. The overhead and precision of the verification in ECS are studied by an optimal sample size strategy. Finally, a prototype system is implemented based on our framework. We conduct a series of experiments to evaluate the effectiveness of the proposed schemes. The experimental results show that our schemes can effectively improve the performance of data integrity verification.

[1]  Jean-Jacques Quisquater,et al.  Remote Integrity Checking - How to Trust Files Stored on Untrusted Servers , 2003, IICIS.

[2]  Liming Zhu,et al.  Blockchain Based Data Integrity Service Framework for IoT Data , 2017, 2017 IEEE International Conference on Web Services (ICWS).

[3]  Cong Wang,et al.  Enabling Public Verifiability and Data Dynamics for Storage Security in Cloud Computing , 2009, ESORICS.

[4]  Roberto Baldoni,et al.  Blockchain-Based Database to Ensure Data Integrity in Cloud Computing Environments , 2017, ITASEC.

[5]  Hovav Shacham,et al.  Compact Proofs of Retrievability , 2008, Journal of Cryptology.

[6]  Reza Curtmola,et al.  Provable data possession at untrusted stores , 2007, CCS '07.

[7]  Reza Curtmola,et al.  MR-PDP: Multiple-Replica Provable Data Possession , 2008, 2008 The 28th International Conference on Distributed Computing Systems.

[8]  Juan Benet,et al.  IPFS - Content Addressed, Versioned, P2P File System , 2014, ArXiv.

[9]  Ivona Brandic,et al.  Efficient Edge Storage Management Based on Near Real-Time Forecasts , 2017, 2017 IEEE 1st International Conference on Fog and Edge Computing (ICFEC).

[10]  Reza Curtmola,et al.  Robust dynamic remote data checking for public clouds , 2012, CCS.

[11]  Anmin Fu,et al.  SeShare: Secure cloud data sharing based on blockchain and public auditing , 2019, Concurr. Comput. Pract. Exp..

[12]  Jianli Pan,et al.  Future Edge Cloud and Edge Computing for Internet of Things Applications , 2018, IEEE Internet of Things Journal.

[13]  Hongjun Dai,et al.  A distributed multi-level model with dynamic replacement for the storage of smart edge computing , 2018, J. Syst. Archit..

[14]  Roberto Di Pietro,et al.  Scalable and efficient provable data possession , 2008, IACR Cryptol. ePrint Arch..

[15]  Josep Domingo-Ferrer,et al.  Efficient Remote Data Possession Checking in Critical Information Infrastructures , 2008, IEEE Transactions on Knowledge and Data Engineering.

[16]  Shui Yu,et al.  Blockchain for secure location verification , 2020, J. Parallel Distributed Comput..

[17]  Ari Juels,et al.  Pors: proofs of retrievability for large files , 2007, CCS '07.

[18]  Xianbin Wang,et al.  Live Data Analytics With Collaborative Edge and Cloud Processing in Wireless IoT Networks , 2017, IEEE Access.

[19]  William Allen,et al.  Data Security, Privacy, Availability and Integrity in Cloud Computing: Issues and Current Solutions , 2016 .

[20]  M. Iansiti,et al.  The Truth about Blockchain , 2017 .