Privacy-Preserving Public Cloud Audit Scheme Supporting Dynamic Data for Unmanned Aerial Vehicles

Abstract

As one of the most popular applications in recent years, cloud storage has been gradually integrated into all walks of life. In the field of communication techniques for the unmanned aerial vehicles (UAVs), UAVs use sensors to upload collected data to cloud servers during various exploration activities, but UAVs can only store and calculate valid information currently collected due to the limited storage and computing performance. In the actual exploration, UAVs need not only to upload complete data to the cloud server, but also to support the data dynamic update efficiently. Moreover, due to security requirements, the privacy of data uploaded by UAVs must be protected. However, the existing auditing schemes for dynamic data and integrity have many problems, such as high computation cost, low efficiency of dynamic update, low privacy and security. For this reason, we propose a public cloud audit scheme that supports dynamic data and privacy protection based on distributed string equality check protocol and Merkle-hash tree multi-level index structure. First of all, a third-party server (TPS) is set between the cloud service provider and users, which complete digital signature, integrity auditing, and data dynamic operations significantly in place of users to reduce the local computing cost. Users then locally upload data which has been encrypted to the TPS. Secondly, to further improve the security of the scheme, TPS implement signature for encrypted data based on the distributed string equality check protocol. By designing authorizations with time constraints, it is guaranteed that only the legitimate TPS with time constraints can operate with cloud servers. Finally, we implement dynamic data operation efficiently based on MHT multi-level index structure. The security proof and performance analysis show that our proposed scheme is safe and effective. INDEX TERMS Cloud Storage, communication techniques for UAVs, privacy-preserving, dynamic updating, intergrity auditing.

Identity-Based Privacy Preserving Remote Data Integrity Checking With a Designated Verifier

“…If the CSP forges the cloud data and tags, it could still pass the verification. Liu et al [29] proposed a public cloud audit scheme that supports dynamic data and privacy protection. However, in this scheme, the data owner first encrypts the data, and then the verifier calculates the digital signature, reducing the security and flexibility of the scheme.…”

“…However, other schemes in Table 1 use public verification that any verifier can perform checking tasks. In terms of privacy protection, schemes in [22], [23], [27] and [30] combines homomorphic verification with random mask, and scheme in [29] encrypts and then signs the data block, all of which ensure that the verifier knows nothing about the data content during the data integrity checking. However, other schemes in Table 1 do not consider that computing the linear combination of data blocks in the data integrity proof may deduce the data content.…”

Privacy-Preserving Cloud Computing: Ecosystem, Life Cycle, Layered Architecture and Future Roadmap

“…As a real world example, unmanned aerial vehicles require an audit scheme to accommodate their limited storage and computing performance. They can use an audit scheme such as the one in [302] using a distributed string equality check and Merkle-hash tree multi-level index structure.…”

Outsourced Auditing With Data Integrity Verification Scheme (OA-DIV) and Dynamic Operations for Cloud Data with Multi-Copies

“…A data integrity scheme for cloud computing environment is presented on the basis of distributed machine learning in [16]. Initially, a Provable Data Possession (PDP) sampling based auditing algorithm is presented for verifying the data integrity.…”

“…This work supports dynamic operations on data as well and the security analysis of the work is performed. In [16], a privacypreserving audit scheme is proposed for cloud computing, which also can support dynamic data operations of Unmanned Aerial Vehicles (UAV). This technique works on the basis of distributed string equality check protocol in addition to Merkle hash tree.…”