Data Integrity Verification Schemes in Cloud Computing Environment: A Survey

The Data Integrity Based Secure Cloud Data Outsourcing Model involves designing a framework that ensures data outsourced to the cloud remains secure, intact, and authentic. Cloud computing has become an indispensable resource for businesses and individuals alike, providing scalable and cost-effective solutions for data storage and management. However, outsourcing data to external cloud service providers (CSPs) raises serious questions around data security, integrity, and authenticity. It is essential to retain confidence and comply with regulatory criteria to make sure that outsourced data is authentic, obtainable, and unaltered. In this article, the Low-Complexity Elliptic Galois Cryptography based Secure Data Integrity Verification Scheme for Cloud Storage (LCEGC-SDIV-CS) is proposed. Initially, the integration of the advantages in Trusted Execution Environment (TEE) and identity-based encryption using Low-Complexity Elliptic Galois Cryptography (LCEGC) is provided to create a safe data integrity verification scheme. Then, data integrity using Block Access Signature Oriented Merle Hash Tree (BS-MHT) is used for the integrity-preserving structure for encrypted block-oriented storage systems. The random Oracle model's security analysis, depending upon the computational Diffie-Hellman assumption, provides security by preventing attacks when the adversary chooses the messages with targets’ identities. The proposed LCEGC-SDIV-CS model is implemented and the performance metrics like Data uploading with downloading time, Memory usage on data uploading with downloading, Encryption time, Decryption time, and Security levels are examined. The proposed LCEGC-SDIV-CS method attains 21.56%, 23.98%, and 21.19% lower data uploading with downloading time 24.78%, 23.82%, and 23.52% lower encryption time are analyzed with existing methods EDI-SPD-SCS, NSA-SADS-BDEPDP-SDS-RCS respectively.

INTRODUCTION: With the rapid development of cloud computing and intelligent technology, traditional accounting informatization systems are gradually migrating to cloud computing platforms, promoting financial management's automation and intelligence. OBJECTIVES: However, data security in the cloud computing environment, especially the issue of data integrity, has become one of the core challenges for intelligent accounting informatization systems. Accounting informatization systems rely on the storage and processing of a large amount of financial, tax, and transaction data, and the integrity of these data is directly related to the financial transparency, compliance, and decision-making accuracy of an enterprise. METHODS: Therefore, how to design an efficient and scalable cloud data integrity verification algorithm becomes the key to ensuring the reliability and security of intelligent accounting systems. This paper proposes a cloud data integrity verification algorithm for smart accounting informationization based on a cloud computing environment. The algorithm combines the efficient data processing capability of cloud computing with the automation requirements of smart accounting systems to ensure data integrity during storage, transmission, and processing through various data validation techniques such as digital signatures, hash algorithms, and blockchain-based distributed ledgers. RESULTS: The algorithm design considers the dynamics and scalability of the cloud computing environment. It can realize fast, real-time data validation and integrity detection in a large-scale data environment. Through experimental verification, the algorithm proposed in this paper performs well in processing large-scale accounting data with high verification efficiency and accuracy. CONCLUSION: Compared with traditional validation methods, the algorithm improves the speed of data validation. It enhances the system's ability to prevent data tampering and loss, providing a new cloud data integrity assurance scheme for intelligent accounting informatization systems.

Cloud computing (CC) services can offer substantial cost-effective global operational and relationship benefits if the cooperation between logistics and CC services are resilient. Potential vulnerabilities to cooperation of CC and logistics service providers can occur with respect to vital factors such as security and trust. Extant studies have demonstrated CC benefits as well as few challenges associated with CC services application. However, no extant study has examined the inter-organisational benefits based on cooperative resilience between CC and logistics service providers in terms of both capability and trust vulnerability factors. This study examines the cooperative resilience of logistics and CC service providers based on innovation diffusion theory within a supply chain risk assessment framework. Using structural equation modelling techniques, we investigate the relationship between the vulnerability factor (trust), capability factor (security) and collaboration benefits (relationship and operational) offered by CC service providers based on 236 Chinese logistics service firms’ perceptions of CC adoption. The results indicate Chinese logistics companies perceive security impediments as a major factor affecting cooperative resilience between logistics service and CC service providers.

Blockchain data-based cloud data integrity protection mechanism

Outsourced data, as the significant component of cloud service, has been widely used due to its convenience, low overhead, and high flexibility. To guarantee the integrity of outsourced data, data owner (DO) usually adopts a third party auditor (TPA) to execute the data integrity verification scheme. However, during the verification process, DO cannot fully confirm the reliability of the TPA, and handing over the verification of data integrity to the untrusted TPA may lead to data security threats. In this paper, we focus on the problem of integrity verification of outsourced data in untrusted environment, that is, how to improve the security and efficiency of data integrity verification without utilizing untrusted TPA. To address the problem, we design a decentralized model based on blockchain consisting of some collaborative verification peers (VPs), each of which maintains a replication of the entire blockchain to avoid maliciously tampering with. Based on the model, we present an advanced data integrity verification algorithm which allows DO to store and check the verification information by writing and retrieving the blockchain. In addition, in order to improve the concurrent performance, we extend the algorithm by introducing the verification group (VG) constituting by some VPs organized by Inner-Group and Inter-Group consensus protocols. We conduct a completed security analysis as well as extensive experiments of our proposed approach, and the evaluation results demonstrate that our proposed approaches achieve superior performance.

<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>

Nowadays, Cloud storage helps the users to remotely store and access the data. Any modification or corruption in data by unauthorized users will lead to insecure cloud framework. Protecting the users data from unauthorized access or malicious attacks in cloud is one of the major research direction to address the issues of data privacy and integrity in cloud. Ensuring cloud data integrity and privacy seems to be the major issue. Inorder to overcome unauthorized access of users data even by Cloud Service Provider (CSP), Data integrity verification is performed through Trusted Third Party Auditor (TTPA). By TTPA, the cloud data auditing need to be performed and data security need to be ensured, without the knowledge of the actual data stored in cloud. Many researchers had keen interest to provide a cloud framework, which preserves the privacy and ensures the integrity of cloud data. In this paper, various researcher ideas based on privacy preservation public auditing schemes has been analyzed as an literature review.

Data integrity is a major concern in outsourced IT services like cloud computing. Cloud computing has become popular because of cost reductions, time saving and mobility in service. However data integrity is still an unresolved issue in cloud services. We present an efficient mechanism for evaluating data integrity in cloud database-as-a-service. Our approach is based on inserting fake tuples into the database. In our model the owner of the data is the only trusted party and the server as a service provider or any other users are not trusted. We refer to distrusted party as a potentially malicious attacker. In our approach we define generating functions to create fake tuples with uniform distribution. Malicious attackers are not able to distinguish between fake tuples and real tuples. Our approach does not use encryption which makes it more efficient. We explore the strengths and limitations of these generating functions by describing our approach.

Moving data and applications to the cloud implies shifting their control from cloud consumers to the cloud service provider (CSP) indefinitely. Hence, the security and privacy (Saamp;P) of the consumers' assets becomes an important issue. Assessing and comparing potential cloud computing (CC) services, poses an issue for CC adopters to choose Saamp;P options that are sufficient and robust at the same time. In this paper, we describe CC adopters' Saamp;P concerns. We identify a set of attributes that reflect various aspects of cloud Saamp;P in an attempt to alleviate those concerns. We classify the attributes based on their tangibility and their relevance to Saamp;P threats. Every attribute in our list is represented by a set of considerations (i.e. polar questions) to assess its quality. We present a tool that embodies our set of attributes. We aim to enable consumers to assess and compare CC services, in terms of Saamp;P, so that they can make well-educated choices. CSPs can also make use of these attributes to offer better cloud Saamp;P.

Resources are provided mainly in the form of services in cloud computing. In the distribute environment of cloud computing, how to find the needed services efficiently and accurately is the most urgent problem in cloud computing. In cloud computing, services are the intermediary of cloud platform, services are connected by lots of service providers and requesters and construct the complex heterogeneous network. The traditional recommendation systems only consider the functional and non-functional requirements of services but ignore the links between providers and requesters of service, which result to the service position is not accurate. Focus on the problems, this study intends to model the relationship of the cloud services participants with the format of heterogeneous information network, which intend to mine the hidden relationships between services participants in the cloud computing environment. In theoretical research, we proposed a cloud service heterogeneous network extraction and automatic maintenance model, proposed a new service recommendation system based on heterogeneous service network ranking and clustering.

DCIV: Decentralized cross-chain data integrity verification with blockchain

Cloud computing is currently emerging as a promising next-generation architecture in the Information Technology (IT) industry and education sector. The encoding process of state information from the data and protection are governed by the organizational access control policies. An encryption technique protects the data confidentiality from the unauthorized access leads to the development of fine-grained access control policies with user attributes. The Attribute-Based Encryption (ABE) verifies the intersection of attributes to the multiple sets. The handling of adding or revoking the users is difficult with respect to changes in policies. The inclusion of multiple encrypted copies for the same key raised the computational cost. This paper proposes an efficient Key Derivation Policy (KDP) for improvement of data security and integrity in the cloud and overcomes the problems in traditional methods. The local key generation process in proposed method includes the data attributes. The secret key is generated from the combination of local keys with the user attribute by a hash function. The original text is recovered from the ciphertext by the decryption process. The key sharing between data owner and user validates the data integrity referred MAC verification process. The proposed efficient KDP with MAC verification analyze the security issues and compared with the Cipher Text–Attribute-Based Encryption (CP-ABE) schemes on the performance parameters of encryption time, computational overhead and the average lifetime of key generation. The major advantage of proposed approach is the updating of public information and easy handling of adding/revoking of users in the cloud.

With the maturity of virtualization technology, the advantages of cloud computing have been gradually apparent with low cost, improvement of resource utilization, energy conservation of service consolidation and convenience of using. Cloud manufacturing provides a huge amount of services and there are kinds of user requirements and devices which are complicated and changeable. So it is necessary that the users quickly develop personalized products to meet their needs. With the popularity of smart phones and the development of 3G technology, the amount of information grows dramatically fast, which makes it a trend to extract information that users are interested in from the world of information, but traditional recommendation methods cant meet the need of people. Starting from information resource requirements of users in the cloud environment, this article discusses the application of cloud computing in personalized information services, analyzes the necessity and feasibility of the cloud computing technology applying to personalized services, proposes the personalized service idea based on cloud computing, and builds a model to introduce cloud computing and cloud service idea to the management and service, hoping to find the integrating point of the cloud computing technology applications in the personalized field.

In recent years cloud computing is getting more and more attention every day. While outsourcing the hardware and software resources, still being able to manage them remotely with benefits like high computing power, competitiveness, cost efficiency, scalability, flexibility, accessibility and availability are revolutionary. For all of its advantages, on the other hand, nothing interesting is ever completely one-sided. Security and integrity of the data which is stored in untrustworthy server is critically important and raises concerns about it. The data can be modified, removed, corrupted or even stolen since it is in the remote server. These kinds of malicious activities can be done either by untrusted server or unauthorized user(s). Therefore, various integrity checking methods have been offered for cloud computing systems. This survey aims to analyze and compare different researches about data integrity proofs for these systems.

Job scheduling system problem is a core and challenging issue in Cloud Computing. How to use Cloud computing resources efficiently and gain the maximum profits with job scheduling. Job scheduling system is one of the Cloud computing service providers’ ultimate goals. In this paper, firstly, by analysis the differentiated QoS requirements of Cloud computing resources users’ jobs, we build the corresponding non-pre-emptive priority M/G/1 queuing model for the jobs.Then, considering Cloud computing service providers’ destination which is to gain the maximum profits by offering Cloud computing resources, we built the system cost function for this queuing model. After that, based on the queuing model and system cost function, considering the goals of both the Cloud Computing service users and providers, we gave the corresponding strategy and algorithm to get the approximate optimistic value of service for each job in the corresponding no-pre-emptive priority M/G/1 queuing model. Finally, we also provide corresponding simulations and numeral results.Analysis and number results show that our approach for job scheduling system can not only guarantee the QoS requirements of the users’ jobs, but also can make the maximum profits for the Cloud computing service providers.While the economic case for cloud computing is compelling, the security challenges it poses are equally striking. In this work we strive to frame the full space of cloud-computing security issues, attempting to separate justified concerns from possible over-reactions. We examine contemporary and historical perspectives from industry, academia, government, and “black hats”. We argue that few cloud computing security issues are fundamentally new or fundamentally intractable; often what appears “new” is so only relative to “traditional”computing of the past several years. Looking back further to the time-sharing era, many of these problems already received attention. On the other hand, we argue that two facets are to some degree new and fundamental to cloud computing: the complexities of multi-party trust considerations, and the ensuing need for mutual audit ability.