Data Integrity Verification Scheme Research Articles

Enhancing Secure and Reliable Data Transfer through Robust Integrity

Cloud computing has emerged as a highly efficient platform that allows multiple users to access various services through virtualization on a shared physical network. The participants in a Cloud Computing (CC) environment include Cloud Service Providers (CSP), Consumers, Brokers, and Auditors. The advantages of cloud storage, such as universal network access, convenience, and scalability, have led to data owners preferring to store their data on remote servers. However, the transfer of outsourced data has become a critical requirement for cloud users due to the availability of different cloud storage services with varying quality of services.
 One major challenge in this context is ensuring the security of secret keys and data integrity. There is no guarantee of data integrity when storing data on an untrusted cloud server. To address this issue, this paper proposes a secure and efficient data integrity verification scheme for cloud storage services. The scheme utilizes a key-homomorphic cryptographic primitive to reduce system complexity and eliminate the need for a public key authentication framework based on a public key infrastructure (PKI) in the data integrity checking protocol. By employing this approach, the proposed method ensures the integrity of remote data stored on cloud servers. Through security analysis and empirical evaluation, it is demonstrated that our scheme is both practical and effective for securely sharing records with multiple owners in cloud computing.

Blockchain based Quantum Resistant Signature Algorithm for Data Integrity Verification in Cloud and Internet of Everything


 INTRODUCTION: The processing and storage capacities of the Internet of Everything (IoE) platform are restricted, but the cloud can readily provide efficient computing resources and scalable storage. The Internet of Everything (IoE) has expanded its capabilities recently by employing cloud resources in multiple ways. Cloud service providers (CSP) offer storage resources where extra data can be stored. These methods can be used to store user data over the CSP while maintaining data integrity and security. The secure storage of data is jeopardized by concerns like malicious system damage, even though the CSP's storage devices are highly centralized. Substantial security advancements have been made recently as a result of using blockchain technology to protect data transported to networks. In addition, the system's inclusive efficacy is enhanced, which lowers costs in comparison to earlier systems.
 OBJECTIVES: The main objective of the study is to a blockchain-based data integrity verification scheme is presented to provide greater scalability and utilization of cloud resources while preventing data from entering the cloud from being corrupted.
 METHODS: In this paper, we propose a novel method of implementing blockchain in order to enhance the security of data stores in cloud.
 RESULTS: The simulations indicate that the proposed approach is more effective in terms of data security and data integrity. Furthermore, the comparative investigation demonstrated that the purported methodology is far more effective and competent than prevailing methodologies.
 CONCLUSIONS: The model evaluations demonstrated that the proposed approach is quite effective in data security.

Blockchain assisted blind signature algorithm with data integrity verification scheme

SummaryAs the demand for cloud storage systems increases, ensuring the security and integrity of cloud data becomes a challenge. Data uploaded to cloud systems are vulnerable to numerous sorts of assaults, which must be handled appropriately to avoid data tampering issues. In addition, quantum computers are expected to be introduced soon, which may face multiple security issues by destroying all traditional cryptosystems. This work introduces a quantum‐resistant blockchain centered data integrity verification system with the use of several techniques. Initially, the keys and signatures are generated by the users with the help of the lattice‐based blind signature algorithm (L_BSA), which is a combination of lattice cryptography and a blind signature algorithm. From the generated random keys, the most optimal key is then selected by the Puzzle Optimization Algorithm (POA), which is then made available to the encryption phase. Then, the upgraded Merkle tree‐assisted vacuum filter (Vac‐UMT) algorithm is executed to accomplish the encryption task. Then the data are converted into blocks using blockchain technology and uploaded to the cloud. When receiving the audit requests, the verification process is carried out, and the evidence report is generated for the users. The proposed work is simulated in JAVA and assessed with the UNSW‐NB15 dataset, and the outcomes demonstrated that the system is highly efficient and secure.

Backdoor-Resistant Public Data Integrity Verification Scheme Based on Smart Contracts

This paper analyzes existing smart contract-based public data integrity verification schemes and identifies certain weaknesses. First, the fair arbitration mechanism deployed in these schemes fails to meet the users’ requirements as it may not promptly notify users of data corruption or loss. Second, to ensure outsourced data confidentiality, existing data integrity schemes use a conventional encrypted method, where each user randomly selects a key to encrypt the outsourced data. Such a method results in varying ciphertexts for the same data by different users, leading to additional storage costs for the cloud server. Third, users’ devices, if poorly designed or even intentionally backdoored, can potentially exfiltrate secrets and compromise the security of schemes. To address these issues, we propose the first backdoor-resistant public data integrity verification scheme based on smart contracts (ASSIST). The key idea is to introduce a new entity (a whistleblower) to periodically monitor the state of verification results recorded in the blockchain. This allows for timely notification of data corruption to users. ASSIST requires users to encrypt their data with a cryptographic primitive called message-locked encryption (MLE), which motivates different users to produce the same ciphertext for the same data and reduces storage costs for cloud servers. We also deploy a cryptographic reverse firewall between users’ devices and the external to re-randomize interactive messages, making the exfiltration impossible. We provide rigorous security proofs to demonstrate the security of ASSIST. The performance evaluation shows that ASSIST is efficient regarding computation and communication costs.

An Efficient and Universal Real-Time Data Integrity Verification Scheme Based on Symmetric Key in Stream Computing System

The integrity of real-time data streams has not been solved for a long time and has gradually become a difficult problem in the field of data security. Most of the current data integrity verification schemes are constructed using cryptographic algorithms with complex computation, which cannot be directly applied to real-time stream computing systems. Aiming at the above issue, this paper adopts the Carter–Wegman MAC method, pseudo-random function and symmetric cryptography mechanism to construct the Real-Time Data Integrity Verification scheme based on symmetric key in stream computing systems (RT-DIV), which converts a one-time MAC to a multiple-time MAC and retains the advantage of security performance. Then, a security analysis is given under the standard model. Finally, experiments and data analysis are conducted in a simulated environment, and the experimental results show that the RT-DIV scheme can effectively guarantee the integrity of real-time data streams. Furthermore, the RT-DIV scheme lays the foundation for the secure application of the stream computing system.

Algebraic Signature-Based Public Data Integrity Batch Verification for Cloud-IoT

With the rapid development of Internet of Things, the related data are growing explosively. However, IoT devices have limited storage and computing capabilities so that they cannot deal with massive data storage and computing locally. The integration of IoT and cloud is regarded as an effective solution to the above issue, i.e., IoT devices outsource collected data to cloud to enjoy powerful storage and computing resources. Because the data stored in cloud are out of the control of IoT users, some security risks need to be addressed in advance. In this paper, we propose a public data integrity verification scheme, called AIVCI, to check the data integrity for Cloud-IoT scenarios. Firstly, based on algebraic signature and homomorphic hash function, AIVCI can efficiently complete data auditing. Secondly, AIVCI adopts blind technology to prevent the privacy leakage of IoT data and further protect the privacy of IoT users. Thirdly, batch auditing is implemented to improve auditing efficiency and meet realistic demands for Cloud-IoT scenarios. And a new data structure named Improved Divide and Conquer Table (ID&CT) is designed to realize efficient data dynamics. Finally, the security and performance analysis demonstrates that AIVCI is more secure and efficient.

Correction: Witanto et al. Distributed Data Integrity Verification Scheme in Multi-Cloud Environment. Sensors 2023, 23, 1623

The authors make the following corrections to the published paper [...]

SM2-Based Offline/Online Efficient Data Integrity Verification Scheme for Multiple Application Scenarios.

With the rapid development of cloud storage and cloud computing technology, users tend to store data in the cloud for more convenient services. In order to ensure the integrity of cloud data, scholars have proposed cloud data integrity verification schemes to protect users' data security. The storage environment of the Internet of Things, in terms of big data and medical big data, demonstrates a stronger demand for data integrity verification schemes, but at the same time, the comprehensive function of data integrity verification schemes is required to be higher. Existing data integrity verification schemes are mostly applied in the cloud storage environment but cannot successfully be applied to the environment of the Internet of Things in the context of big data storage and medical big data storage. To solve this problem when combined with the characteristics and requirements of Internet of Things data storage and medical data storage, we designed an SM2-based offline/online efficient data integrity verification scheme. The resulting scheme uses the SM4 block cryptography algorithm to protect the privacy of the data content and uses a dynamic hash table to realize the dynamic updating of data. Based on the SM2 signature algorithm, the scheme can also realize offline tag generation and batch audits, reducing the computational burden of users. In security proof and efficiency analysis, the scheme has proven to be safe and efficient and can be used in a variety of application scenarios.

A New Data Integrity Verification Scheme with Low Communication Cost

<p>The development of cloud storage is indispensable for today’s Internet information technology. The superiority of cloud storage is that the ownership of the storage medium and the ownership of the stored data are divided and held by two parties with respective interests - cloud server providers and data users. However, the transmission, storage and utilization of data constantly caused the violation of users’ rights and interests. Data integrity as a countermeasure has been paid growing attention to by researchers. Traditional data integrity protection schemes are based on the cloud server-client architecture, which requires high computational overhead and communication. To address this scenario, this paper proposes an improved data integrity verification scheme that enables local users to perform rapid and efficient data integrity verification of data stored on cloud servers, reduces the volume of communication data during the verification process, and effectively prevents the loss or tampering of data stored in the cloud server.</p> <p> </p>

Distributed Data Integrity Verification Scheme in Multi-Cloud Environment.

Most existing data integrity auditing protocols in cloud storage rely on proof of probabilistic data possession. Consequently, the sampling rate of data integrity verification is low to prevent expensive costs to the auditor. However, in the case of a multi-cloud environment, the amount of stored data will be huge. As a result, a higher sampling rate is needed. It will also have an increased cost for the auditor as a consequence. Therefore, this paper proposes a blockchain-based distributed data integrity verification protocol in multi-cloud environments that enables data verification using multi-verifiers. The proposed scheme aims to increase the sampling rate of data verification without increasing the costs significantly. The performance analysis shows that this protocol achieved a lower time consumption required for verification tasks using multi-verifiers than a single verifier. Furthermore, utilizing multi-verifiers also decreases each verifier's computation and communication costs.

A Data Integrity Verification Scheme for Centralized Database Using Smart Contract and Game Theory

Currently, many companies and institutions use centralized or distributed databases to store massive amounts of data. However, the use of untrusted centralized third-party auditors can result in security issues because these auditors may be malicious and tamper with or delete user data. This poses a significant challenge for ensuring the reliability of the data verification results. Although introducing a third-party auditor can help address this issue, it may also be untrustworthy and collude with the database service provider to forge false data verification results. In this study, we propose a data integrity verification scheme using smart contracts (DIV-SC) to address this challenge in a centralized database environment. Our approach utilizes blockchain technology as a decentralized third-party auditor, ensuring that the information stored on the blockchain is immutable and cannot be tampered with maliciously. In addition, smart contracts deployed on the blockchain can ensure that the verification procedures are correct and are not affected by any malicious party. We also leverage game theory to improve the reliability of multiple verifications, reduce verification time and improve overall performance. Our proposed scheme reduces the total verification time consumption by up to 53.44% while increasing the number of verifiable times by nearly 3.8 times, compared to conventional data integrity verification schemes.

Comments on a Dynamic Cloud Data Integrity Verification Scheme: Security Analysis and Improvement

Comments on a Dynamic Cloud Data Integrity Verification Scheme: Security Analysis and Improvement

Comments on a dynamic cloud data integrity verification scheme: security analysis and improvement

To ensure the integrity and reliability of the data on cloud servers, many public data verification schemes have been presented to allow data auditors to remotely audit the data integrity without fetching the data back. Recently, Zhao et al. (2021) proposed a dynamic data integrity audition scheme for cloud computing based on the dynamic array multi-branch tree (MBT). In their scheme, each leaf node x stores a hash value H(x) which relates to all the hash values of blocks in its block array. Because the value H(x) is always used to generate the integrity proof when any block linked to x is challenged, the attacker can deceive the auditor by replacing the challenged block with another one in the same block array. To address this problem of Zhao's scheme, we add a new index i for each block in the block array, which can ensure the uniqueness of each block to resist the replacement attack. Moreover, the algorithms of label generation and proof verification in Zhao's scheme are also upgraded to keep the soundness of the scheme. We give the security proof of the new scheme and make comprehensive performance analyses showing that compared with the original algorithms in Zhao's scheme, only negligible costs such as hash are brought to the new ones.

DCIV: Decentralized cross-chain data integrity verification with blockchain

In recent years, blockchain holds promise to impact a wide range of application areas, but it still suffers from technical challenges such as security and scalability. The increase in the number of transactions puts blockchains under data storage pressure. The emergence of cross-chain technologies connects different blockchains and relieves the data storage pressure. However, the existing research generally focuses on the technical realization of cross chain, lacking in-depth research on consistency issues like data integrity verification of cross-chain interaction. In this paper, we propose a decentralized cross-chain data integrity verification scheme (DCIV) from the point of view of governing the chain by chain. We adopt supervision chain to audit the integrity of data in cross-chain interaction. We preprocess the off-chain original data in the form of Merkle tree. Before cross-chain interaction, we process the data with KZG polynomial commitment. During the auditing period, the supervision chain generates a challenge and verifies the integrity of cross-chain data. In particular, we add audit digests into the structure of transactions in blockchain to reduce the storage burden during auditing. Theoretical and experimental analyses demonstrate that DCIV can verify the integrity of data in cross-chain interaction, achieving secure and accurate cross-chain data sharing.

A blockchain-based dynamic and traceable data integrity verification scheme for smart homes

A smart home system composed of numerous smart devices has benefited people’s life due to the feature of convenience. With the development of smart home technology, huge amounts of data stored on external servers flow between different smart devices, and the integrity of these data is of great importance to the security of smart home systems. In this paper, we propose a blockchain-based data integrity verification scheme that supports efficient dynamic operations for a smart home system. In the verification scheme, we utilize the home gateway (HG) to aggregate all the data information and design a data structure that can be efficiently and dynamically operated to store the tag information of the data, which can reduce the local storage pressure in smart home systems. Moreover, homomorphic verifiable tags are used to formulate verification strategies and record the interactions between HG, cloud service providers (CSP), and third-party auditor (TPA) on the blockchain to make the verification service traceable and useful. Then, the theoretical analysis and experiments prove that the scheme is effective and cost-acceptable in smart home systems.

Edge data integrity verification scheme supporting data dynamics and batch auditing

With the rapid development of 5G technology and wireless networks, new applications such as VR/AR-based immersive online games have developed rapidly. These applications are very sensitive to network delays. To address the time delay of data transfer, the vendors of these delay-sensitive applications often deploy data replicas on edge servers to provide users with a low-latency application experience. However, the edge computing environment is highly distributed and dynamic, which makes the data replicas stored on edge servers often face intentional or unintentional damage. In addition, the computing resources of edge servers are very limited compared to cloud servers. Therefore, how to efficiently audit the integrity of data replicas stored on a large number of edge servers becomes an urgent problem to be solved. This paper first designs a data integrity verification scheme called EDI-DA in edge environment to help application vendors to check the integrity of data replicas stored on distributed edge servers. Then, we extend EDI-DA to allow application vendors to verify the integrity of different edge data replicas simultaneously, i.e., our EDI-DA supports batch auditing of multiple original data. Next, we propose an improved data structure I-SLT based on which EDI-DA supports full data dynamics, including insertion, deletion and modification. Finally, security and performance analyses indicate the security and practicability of our EDI-DA.

A Scalable Blockchain-Based Integrity Verification Scheme

Ensuring the integrity of remote data is the prerequisite for implementing cloud-edge computing. Traditional data integrity verification schemes make users spend a lot of time regularly checking their data, which is not suitable for large-scale IoT (Internet of Things) data. On the other hand, the introduction of a third-party auditor (TPA) may bring about greater privacy and security issues. We use blockchain to address the problem of TPA. However, implementing dynamic integrity verification with blockchain is a bigger challenge due to the low throughput and poor scalability of blockchain. More importantly, whether there is a security problem with blockchain-based integrity verification is not yet known. In this paper, we propose a scalable blockchain-based integrity verification scheme that implements fully dynamic operations and blockless verification. The scheme builds scalable homomorphic verification tags based on ZSS (Zhang-Safavi-Susilo) short signatures. We exploit smart contract technology to replace TPA for integrity verification tasks, which not only eliminates the risk of privacy leakage but also resists collusion attacks. Furthermore, we formally define a blockchain-based security model and prove that our scheme is secure under the security assumption of cryptographic primitives. Finally, the mathematical analysis of our scheme shows that both the communication complexity and the communication complexity of an audit are O c , in which c is the number of challenge blocks. We compare our scheme with other schemes, and the results show that our scheme has the lowest time consumption to complete an audit.

HB+-MHT: Lightweight and Efficient Data Integrity Verification Scheme for Cloud Virtual Machines

With the rapid development of cloud computing, cloud storage is widely used. In the cloud environment, users’ virtual machine system mirrors and data are stored in the cloud server. The escape of virtual machines and Trojan virus attacks make it challenging to ensure the integrity of virtual machine systems. Trusted computing is expensive to randomly verify data integrity and does not adapt to dynamic data changes. Provable data integrity is a potential solution to this problem. Merkle Hash Tree (MHT) model is widely adopted in provable data integrity. Although MHT requires only a small amount of evidence for verification, the verifier’s number of hash calculations and the server’s efficiency of evidence query are not optimal. Moreover, the verification frequency of each piece of data is not considered by MHT. Properly handling these factors can improve the actual verification performance. In this paper, a lightweight and efficient data integrity verification approach called HB+-MHT is proposed for the tenant virtual machine (TVM) in cloud computing. In HB+-MHT, the Huffman hash tree scheme is used for small file verification to ensure that the hot file has a shorter path, which reduces the required amount of evidence for verification. Meanwhile, the B+ hash tree scheme is used for big files verification, which can effectively reduce evidence query time and hash calculation times. The experimental results show that the scheme proposed in this paper can perform data integrity verification well, with reduced computing and storage overhead.

An Innovative Data Integrity Verification Scheme in the Internet of Things assisted information exchange in transportation systems

An Innovative Data Integrity Verification Scheme in the Internet of Things assisted information exchange in transportation systems

Identity-based public data integrity verification scheme in cloud storage system via blockchain

Identity-based public data integrity verification scheme in cloud storage system via blockchain