Abstract
With the explosive growth in the number of IoT devices, ensuring the integrity of the massive data generated by these devices has become an important issue. Due to the limitation of hardware, most past data integrity verification schemes randomly select partial data blocks and then perform integrity validation on those blocks instead of examining the entire dataset. This will result in that unsampled data blocks cannot be detected even if they are tampered with. To solve this problem, we propose a new and effective integrity auditing mechanism of sensor data based on a bilinear map accumulator. Using the proposed approach will examine all the data blocks in the dataset, not just some of the data blocks, thus, eliminating the possibility of any cloud manipulation. Compared with other schemes, our proposed solution has been proved to be highly secure for all necessary security requirements, including tag forgery, data deletion, replacement, replay, and data leakage attacks. The solution reduces the computational and storage costs of cloud storage providers and verifiers, and also supports dynamic operations for data owners to insert, delete, and update data by using a tag index table (TIT). Compared with existing schemes based on RSA accumulator, our scheme has the advantages of fast verification and witness generation and no need to map data blocks to prime numbers. The new solution supports all the characteristics of a data integrity verification scheme.
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Index Terms
Integrity Verification Mechanism of Sensor Data Based on Bilinear Map Accumulator
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