Fibonacci tree structure based privacy preserving public auditing for IoT enabled data in cloud environment

Abstract

Presently, Internet of Things (IoT) adopts cloud storage services to facilitate the efficient integration of IoT devices and the seamless management of collected data. Nevertheless, data owners have no direct control over outsourced data in the cloud storage model, leading to substantial data integrity issues. Earlier, many public auditing models have been introduced to ensure data integrity in the cloud environment. However, these models cannot guarantee - data dynamics with proper retrievability and privacy-preservation against trusted third party auditor (TPA) during auditing procedure. To address the limitations of public auditing models, we introduce a Fibonacci Tree (FT) structure-based efficient public auditing model supporting dynamic data updates with a standard security model. Specifically, Fibonacci Tree (FT) structure is designed to achieve real-time data updates with proper data traceability. The proposed model also includes an extended index-hash-table (E-IHT) located at TPA and records the data block's properties for efficient data dynamics and auditing procedure. The comprehensive security analysis with standard proof guarantees the computational intractability of the proposed model. At last, the experimental analysis demonstrates the feasibility and practicability of the proposed model.