scholarly journals Comparable Encryption Scheme over Encrypted Cloud Data in Internet of Everything

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Qian Meng ◽  
Jianfeng Ma ◽  
Kefei Chen ◽  
Yinbin Miao ◽  
Tengfei Yang
Keyword(s):  
Model Performance ◽  
Data Integrity ◽  
Cloud Service ◽  
Third Party ◽  
Encryption Scheme ◽  
Cloud Data ◽  
Practical Applications ◽  
Internet Of Everything ◽  
Window Method ◽  
Comparable Encryption

User authentication has been widely deployed to prevent unauthorized access in the new era of Internet of Everything (IOE). When user passes the legal authentication, he/she can do series of operations in database. We mainly concern issues of data security and comparable queries over ciphertexts in IOE. In traditional database, a Short Comparable Encryption (SCE) scheme has been widely used by authorized users to conduct comparable queries over ciphertexts, but existing SCE schemes still incur high storage and computational overhead as well as economic burden. In this paper, we first propose a basic Short Comparable Encryption scheme based on sliding window method (SCESW), which can significantly reduce computational and storage burden as well as enhance work efficiency. Unfortunately, as the cloud service provider is a semitrusted third party, public auditing mechanism needs to be furnished to protect data integrity. To further protect data integrity and reduce management overhead, we present an enhanced SCESW scheme based on position-aware Merkle tree, namely, PT-SCESW. Security analysis proves that PT-SCESW and SCESW schemes can guarantee completeness and weak indistinguishability in standard model. Performance evaluation indicates that PT-SCESW scheme is efficient and feasible in practical applications, especially for smarter and smaller computing devices in IOE.

scholarly journals Cloud Data Integrity Verification Algorithm for Sustainable Accounting Informatization

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lin Yang
Keyword(s):  
Big Data ◽  
Execution Time ◽  
Cloud Storage ◽  
Computing Time ◽  
Data Integrity ◽  
Cloud Data ◽  
Integrity Verification ◽  
Verification Algorithm ◽  
Advantages And Disadvantages ◽  
Better Than

In recent years, people have paid more and more attention to cloud data. However, because users do not have absolute control over the data stored on the cloud server, it is necessary for the cloud storage server to provide evidence that the data are completely saved to maintain their control over the data. Give users all management rights, users can independently install operating systems and applications and can choose self-service platforms and various remote management tools to manage and control the host according to personal habits. This paper mainly introduces the cloud data integrity verification algorithm of sustainable computing accounting informatization and studies the advantages and disadvantages of the existing data integrity proof mechanism and the new requirements under the cloud storage environment. In this paper, an LBT-based big data integrity proof mechanism is proposed, which introduces a multibranch path tree as the data structure used in the data integrity proof mechanism and proposes a multibranch path structure with rank and data integrity detection algorithm. In this paper, the proposed data integrity verification algorithm and two other integrity verification algorithms are used for simulation experiments. The experimental results show that the proposed scheme is about 10% better than scheme 1 and about 5% better than scheme 2 in computing time of 500 data blocks; in the change of operation data block time, the execution time of scheme 1 and scheme 2 increases with the increase of data blocks. The execution time of the proposed scheme remains unchanged, and the computational cost of the proposed scheme is also better than that of scheme 1 and scheme 2. The scheme in this paper not only can verify the integrity of cloud storage data but also has certain verification advantages, which has a certain significance in the application of big data integrity verification.

scholarly journals Hierarchical remote data possession checking method based on massive cloud files

2016 ◽  
Vol 11 (2) ◽  
pp. 126-134
Author(s):  
Ma Haifeng ◽  
Gao Zhenguo ◽  
Yao Nianmin
Keyword(s):  
Cloud Storage ◽  
False Negative ◽  
False Negative Rate ◽  
Data Integrity ◽  
Communication Overhead ◽  
Local Data ◽  
Cloud Data ◽  
Cloud Storage Service ◽  
Integrity Protection ◽  
Remote Data

Cloud storage service enables users to migrate their data and applications to the cloud, which saves the local data maintenance and brings great convenience to the users. But in cloud storage, the storage servers may not be fully trustworthy. How to verify the integrity of cloud data with lower overhead for users has become an increasingly concerned problem. Many remote data integrity protection methods have been proposed, but these methods authenticated cloud files one by one when verifying multiple files. Therefore, the computation and communication overhead are still high. Aiming at this problem, a hierarchical remote data possession checking (hierarchical-remote data possession checking (H-RDPC)) method is proposed, which can provide efficient and secure remote data integrity protection and can support dynamic data operations. This paper gives the algorithm descriptions, security, and false negative rate analysis of H-RDPC. The security analysis and experimental performance evaluation results show that the proposed H-RDPC is efficient and reliable in verifying massive cloud files, and it has 32–81% improvement in performance compared with RDPC.

Merkle Tree and Blockchain-Based Cloud Data Auditing

2020 ◽  
Vol 10 (3) ◽  
pp. 54-66
Author(s):  
Arun Prasad Mohan ◽  
Mohamed Asfak R. ◽  
Angelin Gladston
Keyword(s):  
Data Integrity ◽  
Service Provisioning ◽  
Merkle Tree ◽  
Cloud Data ◽  
Integrity Checking ◽  
Dataset Size ◽  
Data Auditing ◽  
Core Idea ◽  
Cloud Audit ◽  
Verification Techniques

Cloud computing is the fastest growing and most promising field in the service provisioning segment. It has become a challenging task to provide security in the cloud. The purpose of this article is to suggest a better and efficient integrity verification technique for data referred to as cloud audit. The deployment of cloud storage services has significant benefits in the management of data for users. However, this raises many security concerns, and one of them is data integrity. Though public verification techniques serve the purpose they are vulnerable to procrastinating auditors who may not perform verifications on time. In this article, a cloud data auditing system is proposed. The proposed cloud data auditing system integrates Merkle Tree-based Cloud audit and the blockchain-based audit recording system, thus the core idea is to record each verification result into a blockchain as a transaction. Utilizing the time-sensitive nature of blockchain, the verifications are time-stamped after the corresponding transaction is recorded into the blockchain, which enables users to check whether auditors have performed the verifications at the prescribed time. The proposed cloud data auditing system is experimentally validated. The investigations with varied dataset size revealed less time taken, on an average of 0.25 milliseconds with the use of Merkle Tree. Further results reveal consistency of the data integrity checking.

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