Data Integrity Verification Research Articles

Towards Lightweight Provable Data Possession for Cloud Storage Using Indistinguishability Obfuscation

Cloud Computing has proved to be a boon for many individuals and organizations who cannot afford infrastructure and maintenance cost of resources. But the untrusted nature of Cloud Server (CS) brings many challenges related to security and trust. Public auditing is one process that enables users to delegate the integrity verification of outsourced data to external party such as Third-Party Auditor (TPA). Provable Data Possession (PDP) is one approach of auditing that can verify the integrity using cryptographic algorithms. Many PDP schemes are based on bilinear pairing and homomorphic authenticators that involves complex computations that leads to increased verification time. The lightweight auditing processes is a need today using modern cryptographic techniques. Indistinguishability Obfuscation (IO) is one of the modern but weaker primitive that, if used with one-way functions, provide multiple cryptographic constructs. Sahai and Waters proposed construction of cryptographic constructs using IO. Zhang <i>et al.</i> proposed lightweight public auditing scheme using these IO. But still there are many goals to achieve such as group support, collusion handling, privacy-preserving etc. using IO. In this paper, we are trying to explore these issues and lists future research directions in this field.

A SERM based framework for defining and processing rules supporting the verification of data consistency and integrity

The SERM (Structured Entity Relationship Diagram) data model is a hierarchical extension of the classic ER (Entity Relationship) model. The hierarchical structure of the SERM diagram means that any closed circuit relationship can cause inconsistency and lack of data integrity. The occurrence of these problems is uncertain and should be systematically investigated. Therefore, there is a clear need to develop an approach supporting the definition of logical rules that would control these elements. The aim of the article is to present the framework supporting the intelligent design of relational databases. Its main aspects include identification and semi-automatic handling of logical rules based on the SERM model. An important advantage of the approach is that it does not limit itself to building a semantic data model, but also uses it to design database programming objects such as procedures, functions and triggers that guard the consistency of databases.

An Identity-Based Data Integrity Auditing Scheme for Cloud-Based Maritime Transportation Systems

With the development of Internet of Things (IoT)-enabled Maritime Transportation Systems (MTS), massive data generated in the system not only requires to be stored reliably and cheaply, but also needs to be analyzed timely. The Cloud-based Maritime Transportation Systems (CMTS) allow users to upload the data without worrying about the price, capacity, location and so on. However, CMTS also brings some security issues, where the integrity protection of outsourced data is one of the most important issues since it is crucial for the safety, reliability and efficiency of sea lanes. To solve this problem, we propose an identity-based dynamic data integrity auditing scheme for CMTS. Our scheme decreases the burden of key management and improves the auditing efficiency by batch auditing. Besides, our scheme also supports dynamic operations on the outsourced data for CMTS. The security analysis shows that our scheme can ensure the feature of storage correctness and resist common attacks. In addition, the performance comparison results with other related schemes show that our scheme not only has the lowest computational cost on all entities, but also greatly reduces the communication overhead of the auditing phase. Therefore, our scheme is very suitable for data integrity verification in CMTS.

DOPIV: Post-Quantum Secure Identity-Based Data Outsourcing with Public Integrity Verification in Cloud Storage

Public verification enables cloud users to employ a third party auditor (TPA) to check the data integrity. However, recent breakthrough results on quantum computers indicate that applying quantum computers in clouds would be realized. A majority of existing public verification schemes are based on conventional hardness assumptions, which are vulnerable to adversaries equipped with quantum computers in the near future. Moreover, new security issues need to be solved when an original data owner is restricted or cannot access the remote cloud server flexibly. In this paper, we propose an efficient identity-based data outsourcing with public integrity verification scheme (DOPIV) in cloud storage. DOPIV is designed on lattice-based cryptography, which achieves post-quantum security. DOPIV enables an original data owner to delegate a proxy to generate the signatures of data and outsource them to the cloud server. Any TPA can perform data integrity verification efficiently on behalf of the original data owner, without retrieving the entire data set. Additionally, DOPIV possesses the advantages of being identity-based systems, avoiding complex certificate management procedures. We provide security proofs of DOPIV in the random oracle model, and conduct a comprehensive performance evaluation to show that DOPIV is more practical in post-quantum secure cloud storage systems.

Consensus Mechanism of Blockchain Based on PoR with Data Deduplication

As the basis of cloud computing, distributed storage technology mainly studies how data centers store, organize and manage data. Blockchain has become the most secure solution for cloud storage due to its decentralization and immutability. Consensus mechanism is one of the core technologies of blockchain, which affects the transaction processing capability, security and scalability of blockchain. The current mainstream consensus algorithms such as Proof of Work, Proof of Stake, and Delegated Proof of Stake all have the problem of wasting resources. And with the explosive growth of data, cloud storage nodes store a large amount of redundant data, which inevitably increases storage overhead and computing cost. To this end, we propose to use the Proof of Retrievability with deduplication algorithm as the consensus mechanism of the blockchain system and design a blockchain consensus protocol suitable for distributed storage. First, the data integrity verification protocol in the scheme guarantees that storage nodes correctly store the data they promise to store. Second, the deduplication algorithm in the protocol can optimize data auditing, greatly reduce the need for data storage space, and improve the scalability of data transmission. In addition, the scheme uses ring signatures in the audit process to ensure user anonymity and data unlinkability, while providing highly reliable data storage, and ensuring data storage security through blockchain. Finally, we demonstrate the security of the proposed scheme and evaluate its performance. The evaluation results show that our scheme is efficient and scalable.

Dynamic and Traceable Data Integrity Verification Scheme for a Smart Home System

Dynamic and Traceable Data Integrity Verification Scheme for a Smart Home System

Privacy-Preserving Data Integrity Verification for Secure Mobile Edge Storage

Mobile edge computing (MEC) is proposed as an extension of cloud computing in the scenarios where the end devices desire better services in terms of response time. Because the edges are usually owned by individuals or small organizations with limited operation capabilities, the data on the edges are easily corrupted (due to external attacks or internal hardware failures). Therefore, it is essential to verify data integrity in the MEC. We propose two Integrity Checking protocols for the mobile Edge storage, called ICE-basic and ICE-batch. Our protocols allow a third-party verifier to check the data integrity on the edges without violating users data privacy and query pattern privacy. We rigorously prove the security and privacy guarantees of the protocols. In addition, we have investigated how to let the end devices cache some verification tags such that the communication cost between end devices and the cloud can be further reduced when a user connects to multiple edges in sequence. We have implemented a proof-of-concept system that runs ICE, and extensive experiments are conducted to evaluate the performance of the proposed protocols. The theoretical analysis and experimental results demonstrate the proposed protocols are efficient both in computation and communication.

Опыт сетевого моделирования и картографирования на основе пространственно-временной базы данных по магистральным электрическим сетям

A unique spatio-temporal database of the backbone electric networks of the Moscow power system was previously based on various information sources and published as a cartographic web service. In this study, we consider some mapping possibilities based on calculated parameters, including network analysis methods. To represent the data correctly for each studied year from 1936 to 2020, we have developed algorithms for verifying data integrity, as well as for automated creation of a topologically correct network model. Bringing the network to a topologically correct form implies the snapping of the end vertices of the lines to the point objects of the power system, the elimination of hanging dangles, as well as the elimination of self-intersections. The integrity check is carried out in three stages: 1) coordination of the time frame for the existence of network segments; 2) checking the connectivity of each power line for each time slice; 3) checking the connectivity of the entire network as a whole for each year. The age of the network, betweenness centrality, electric grid centrality, closeness centrality in this paper are taken as an example of local parameters, i. e. indicators confined to specific elements of the network (edges or vertices). In addition, we have considered a global indicator characterizing the network as a whole—the average shortest path in the network, which can be calculated in three ways: without taking into account the weight, taking into account the length of the lines or taking into account its capacitance characteristics, depending on voltage.

A fine‐grained and traceable multidomain secure data‐sharing model for intelligent terminals in edge‐cloud collaboration scenarios

Secure data-sharing technology is a bridge for various collaborative operations among intelligent terminals in the edge-cloud collaborative application scenario. For the shared data involves different levels of confidentiality, intelligent terminals for collaborative operations may be distributed in multiple management domains, and the private information of intelligent terminals is easy to be leaked in edge-cloud collaboration scenarios, the security of data sharing is severely threatened. To solve these problems, this paper proposed a fine-grained and traceable multidomain secure data-sharing model for intelligent terminals. In this model, a key self-certification algorithm is proposed, which avoids potential security threats of key leakage during the key distribution process. The model combines attribute encryption and threshold function to achieve more fine-grained and more flexible secure data sharing; it uses blockchain technology to achieve integrity verification of stored data and traceability of shared data, and it combines on-chain and off-chain databases to achieve rapid retrieval and positioning of shared data distributed among multiple domains, which improves the efficiency of data sharing among domains. The security of the model proposed by us is proved, and compared with the cited literature, it is shown that the proposed model has certain advantages in terms of computational complexity and time consumption.

Enable data privacy, dynamics, and batch in public auditing scheme for cloud storage system

AbstractWith the popularity of cloud computing, cloud storage technology has also been widely used. Among them, data integrity verification is a hot research topic. At present, the realization of public auditing has become the development trend of integrity verification. Most existing public auditing schemes rarely consider some indispensable functions at the same time. Thus, in this article, we propose a comprehensive public auditing scheme (PDBPA) that can simultaneously support data privacy protection, data dynamics, and multi‐user batch auditing. To guarantee privacy protection during the audit process, our PDBPA design a new method of constructing audit proof, which combines random masking techniques and bilinear properties of bilinear pairing. Not only can it ensure that TPA performs audits correctly, but it can also prevent it from exploring the user's sensitive data. In addition, by utilizing the modified dynamic hash table, which is a novel and small two‐dimensional data structure, data dynamics can be effectively achieved. Furthermore, we provide a detailed process for the third‐party auditors to perform batch audits for multiple users. Moreover, we give the detailed and rigorous security analysis in defending against forgery attack, replace attack, and replay attack. Performance evaluations demonstrate that our PDBPA scheme is effective and feasible.

Identity-Based Dynamic Data Auditing for Big Data Storage

Identity-based remote data auditing schemes can verify data integrity and provide a simple identity authentication and management for multiple users. However, prior works on identity-based remote data auditing lack the support of dynamic operations. In these schemes, tag generation is linked to the index of data block, which is related to update operations such as modification, insertion and deletion. If users perform dynamic operations on a data block, the tags of all subsequent blocks need to be modified. It means that if users want to update data on a big data platform, they have to download the whole file, update the file and send the updated file to the big data platform. Such pattern will bring huge communication overhead. In this paper, we propose an identity-based dynamic data auditing scheme which supports dynamic data operations, including modification, insertion and deletion. As far as we know, there is still no other identity-based data auditing scheme that supports dynamic operations. In particular, to achieve efficient dynamic operations, we use the data structure of Merkle hash tree for block tag authentication, which helps update data with integrity assurance. Analyses of security and performance show that the proposed scheme is efficient and secure.

Blockchain-based Integrity Verification of Data Migration in Multi-cloud Storage

In the process of multi-cloud storage data migration, data integrity is vulnerable to corruption, but the existing data integrity verification schemes for data migration across clouds are not highly reliable. To address this problem, a blockchain-based data integrity verification scheme for migration across clouds is proposed in this paper. In this scheme, a blockchain network is used instead of a third-party auditor. For each migration, a multi-cloud broker will send an integrity verification request to blockchain at three different times, and a smart contract will verify the data integrity according to the RSA-based homomorphic verification tags. Then, the security of the scheme is analyzed. Finally, simulation experiments and tests are conducted on Ethereum, and the results show the feasibility of the scheme.

Cloud Data Integrity Verification Algorithm for Sustainable Accounting Informatization

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.

Retraction Note: The abnormal precipitation in rainy season based on genetic algorithm and the security of big data in network

In this paper, cloudsim cloud simulation tool is studied, and its running environment is reasonably configured. Taking the platform as the background, the improved genetic algorithm proposed in this paper is used for simulation experiment that is to optimize the genetic algorithm through simulated annealing behavior. Through the simulation experiment of the improved genetic algorithm, it can be known that the genetic algorithm designed in this paper can satisfy multiple customers one by one and has a certain improvement effect on cloud service quality. In this paper, the problem of rainfall anomaly in city D is studied. The results show that the rainfall anomaly of city D is related to solar activity, 500hPa height field in winter and SST in the Central South Pacific from June to August of the previous year. It is found that there is almost no rainfall during the high solar activity years, while there is frequent rainfall near the low solar activity years. Finally, according to the homomorphic encryption mechanism, this paper studies the protection of data confidentiality in computer network security and the multistorage technology of big data. In this research scheme, by adding a certain number of virtual objects to two different computing information dummies, we successfully protect the data such as the number of items owned by the data owner, the content of the items owned, and the item objects called by the user. In addition, this paper uses bilinear mapping and RS coding technology to create related protocols to solve some problems, such as infinite verification of big data integrity, error data recovery, and protection of data owner’s computing resources. Through the design of solutions to the above problems, this paper successfully completed the protection of big data resources and network security based on cloud computing environment.

Enabling Decentralized and Dynamic Data Integrity Verification for Secure Cloud Storage via T-Merkle Hash Tree Based Blockchain

Cloud storage provides elastic storage services for enterprises and individuals remotely. However, security problems such as data integrity are becoming a major obstacle. Recently, blockchain-based verification approaches have been extensively studied to get rid of a centralized third-party auditor. Most of these schemes suffer from poor scalability and low search efficiency and even fail to support data dynamic update operations on blockchain, which limits their large-scale and practical applications. In this work, we propose a blockchain-based dynamic data integrity verification scheme for cloud storage with T-Merkle hash tree. A decentralized scheme is proposed to eliminate the restrictions of previous centralized schemes. The data tags are generated by the technique of ZSS short signature and stored on blockchain. An improved verification method is designed to check the integrity of cloud data by transferring computation from a verifier to cloud server and blockchain. Furthermore, a storage structure called T-Merkle hash tree which is built based on T-tree and Merkle hash tree is designed to improve storage utilization of blockchain and support binary search on chain. Moreover, we achieve efficient and secure dynamic update operations on blockchain by an append-only manner. Besides, we extend our scheme to support batch verification to handle massive tasks simultaneously; thus, the efficiency is improved and communication cost is reduced. Finally, we implemented a prototype system based on Hyperledger Fabric to validate our scheme. Security analysis and performance studies show that the proposed scheme is secure and efficient.

Data integrity verification using HDFS framework in data flow material environment using cloud computing

A distributed computing platform is preferred to meet out the current challenges of cloud computing paradigm. Hadoop manages distribution of large volume of big data and data is stored using cluster analysis of data. Hadoop Distributed File System (HDFS) is used to manage the problems in handling big data. HDFS can easily store large terabytes of data using commodity servers. The proposed system provides efficient data integrity verification service for big data management based on HDFS. HDFS has data integrity commitment, since it handles large volumes of data. Hadoop HDFS framework uses CRC-32C checksum verification on data node of content blocks to identify data corruption. A data aware module is implemented in Hadoop which provides more clustering process and reduces the computing performances of server. A broad range of data types is analyzed and clustered. The proposed research work uses balanced and proxy encryption technique using Cloud me tool and gives optimized query time and resource usage.

Hash Algorithm In Verification Of Certificate Data Integrity And Security

The hash function is the most important cryptographic primitive function and is an integral part of the blockchain data structure. Hashes are often used in cryptographic protocols, information security applications such as Digital Signatures and message authentication codes (MACs). In the current development of certificate data security, there are 2 (two) types of hashes that are widely applied, namely, MD and SHA. However, when it comes to efficiency, in this study the hash type SHA-256 is used because it can be calculated faster with a better level of security. In the hypothesis, the Merkle-Damgård construction method is also proposed to support data integrity verification. Moreover, a cryptographic hash function is a one-way function that converts input data of arbitrary length and produces output of a fixed length so that it can be used to securely authenticate users without storing passwords locally. Since basically, cryptographic hash functions have many different uses in various situations, this research resulted in the use of hash algorithms in verifying the integrity and authenticity of certificate information.

Research on Data Integrity Verification Technology Based on Blockchain

With the rapid development of Internet of Things technology, it has changed People’s Daily production and life to a great extent, but the large number of applications of Internet of Things devices affect the security level of data to a certain extent. In order to ensure data integrity in the Internet of Things environment, it is necessary to conduct in-depth research on blockchain-based data integrity verification technology, analyze the authenticity structure based on data sources, and carry out data integrity verification exploration according to data source identification structure. The experimental system for data integrity verification is proposed. In this way, the effectiveness of blockchain-based data integrity verification technology can be guaranteed, and the integrity of data can be guaranteed under the condition of decentralization, while the scattered storage of data and data privacy can be protected.

Asset logging in the energy sector: a scalable blockchain-based data platform

Due to a steeply growing number of energy assets, the increasingly decentralized and segmented energy sector fuels the potential for new digital use cases. In this paper, we focus our attention on the application field of asset logging, which addresses the collection, documentation, and usage of relevant asset data for direct or later verification. We identified a number of promising use cases that so far have not been implemented; supposedly due to the lack of a suitable technical infrastructure. Besides the high degree of complexity associated with various stakeholders and the diversity of assets involved, the main challenge we found in asset logging use cases is to guarantee the tamper-resistance and integrity of the stored data while meeting scalability, addressing cost requirements, and protecting sensitive data. Against this backdrop, we present a blockchain-based platform and argue that it can meet all identified requirements. Our proposed technical solution hierarchically aggregates data in Merkle trees and leverages Merkle proofs for the efficient and privacy-preserving verification of data integrity, thereby ensuring scalability even for highly frequent data logging. By connecting all stakeholders and assets involved on the platform through bilateral and authenticated communication channels and adding a blockchain as a shared foundation of trust, we implement a wide range of asset logging use cases and provide the basis for leveraging platform effects in future use cases that build on verifiable data. Along with the technical aspects of our solution, we discuss the challenges of its practical implementation in the energy sector and the next steps for testing in a regulatory sandbox approach.

RETRACTED ARTICLE: The abnormal precipitation in rainy season based on genetic algorithm and the security of big data in network

In this paper, cloudsim cloud simulation tool is studied, and its running environment is reasonably configured. Taking the platform as the background, the improved genetic algorithm proposed in this paper is used for simulation experiment that is to optimize the genetic algorithm through simulated annealing behavior. Through the simulation experiment of the improved genetic algorithm, it can be known that the genetic algorithm designed in this paper can satisfy multiple customers one by one and has a certain improvement effect on cloud service quality. In this paper, the problem of rainfall anomaly in city D is studied. The results show that the rainfall anomaly of city D is related to solar activity, 500hPa height field in winter and SST in the Central South Pacific from June to August of the previous year. It is found that there is almost no rainfall during the high solar activity years, while there is frequent rainfall near the low solar activity years. Finally, according to the homomorphic encryption mechanism, this paper studies the protection of data confidentiality in computer network security and the multistorage technology of big data. In this research scheme, by adding a certain number of virtual objects to two different computing information dummies, we successfully protect the data such as the number of items owned by the data owner, the content of the items owned, and the item objects called by the user. In addition, this paper uses bilinear mapping and RS coding technology to create related protocols to solve some problems, such as infinite verification of big data integrity, error data recovery, and protection of data owner’s computing resources. Through the design of solutions to the above problems, this paper successfully completed the protection of big data resources and network security based on cloud computing environment.