Blockchain data-based cloud data integrity protection mechanism

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.

Even though cloud computing has advanced over the years, the two major challenges currently faced by cloud computing are data security and trusted computing. In cloud computing applications, blockchain technology can enhance data security and trusted computing when paired with virtual machine agents and mobile agent technologies. A decentralized new framework for distributed computing is blockchain. A potential area of study is the integration of blockchain technology with cloud computing, leveraging the former's security mechanisms to enhance the latter's secure computing and storage capabilities. The usage of the proposed framework builds on the inherent security features of blockchain technology in an effort to secure data and information integrity, confidentiality and authentication in cloud environments. Through the introduction of distributed virtual machine agents, the framework increases the scalability and effectiveness of data protection mechanisms for virtual data environments that can be used to store information protected by cloud security measures. Thus, the proposed study substantiates the applicability and efficiency of the existing and emerging problems of cloud data security and this approach develops satisfactory data protection solutions.

SummaryCloud Computing (CC) and big data are growing technology in the business. Big data is demonstrated in terms of volume, variety, and velocity. CC is employed for storing, processing, and accessing data. Many cryptographic techniques have been developed to enhance big data security in cloud computing. However, security and privacy are the primary concerns in protecting data, as it is highly sensitive. Yet, it faces the major problems of inefficient performance, increased time consumption, and lack of data confidentiality and integrity. To address this issue, proposed Extreme Learning with Projection Relational Algebraic Secured Data Transmission (ELPRA‐SDT) is introduced to secure data transactions from cloud users to cloud servers with enhanced data confidentiality and reduced time consumption for big cloud data. The proposed ELPRA‐SDT consists of two major processes namely registration and key generation. At first, the user's IP address is registered employing a transitive advanced set relation theory graph model in a cloud server (CS) for retrieving the numerous services. The CS generates private and public keys for each registered user's IP address using the Transitive Operational and Time Synchronized Random Winternitz Key generation model. After, the user sends a request to the CS for acquiring data. The CS validates the requested user based on security policy attributes. Second, the Projection Relational Algebraic Signcryption and Unsigncryption algorithm performs signature verification to ensure secure data access for protecting the data. Results of experiments carried out by using Coburg Intrusion Detection Data Sets‐001 dataset in Java. ELPRA‐SDT method is more efficient and more suitable for providing security and privacy to network traces in the Cloud. The result shows maximum performance with data confidentiality by 10% and data integrity by 13%. In addition, delay is reduced by 32%, and data delivery time and communication complexity is decreased by 28% and 24% to other existing methods.

Abstract: Encryption is essential in preventing unauthorized access to sensitive data in light of the growing concerns about data security in cloud computing. Homomorphic encryption promises to enable secure calculations on encrypted data without the need for decryption, particularly for cloud-based operations. To evaluate the effectiveness and applicability of several homomorphic encryption algorithms for safe cloud computing, we compare and contrast them in this research paper. Partially homomorphic encryption (PHE), somewhat homomorphic encryption (SHE), and fully homomorphic encryption (FHE) are the three basic homomorphic encryption subtypes that we examine. The implications of this study can aid cloud service providers and organizations in selecting the most appropriate homomorphic encryption scheme based on their specific security requirements and performance considerations. The research contributes to the ongoing efforts to enhance data privacy in cloud computing environments, opening new possibilities for secure data processing in an increasingly connected digital world. The exploration of homomorphic encryption schemes in this study opens new avenues for research and development in the field of cryptographic techniques. As technology continues to evolve, so too must our approaches to safeguarding data. This research serves as a catalyst for further innovations in homomorphic encryption algorithms, enabling even more efficient and robust methods for secure data processing in cloud environments and beyond. The insights derived from this research paper not only empower cloud service providers and organizations to make informed decisions about selecting the most appropriate homomorphic encryption scheme but also contribute to the broader mission of fortifying data privacy and security in cloud computing.

Recent modern era becomes a multi-user environment. It's hard to store and retrieve data in secure manner at the end user side is a hectic challenge. Difference of Cloud computing compare to Network Computing can be accessed from multiple company servers. Cloud computing makes the users and organization to opt their services. Due to effective growth of the Cloud Technology. Data security, Data Privacy key validation and tracing of user are severe concern. It is hard to trace malicious users who misuse the secrecy. To reduce the rate of misuse in secrecy user revocation is used. Audit Log helps in Maintaining the history of malicious user also helps in maintaining the data integrity in cloud. Cloud Monitoring Metrics helps in the evaluation survey study of different Metrics. In this paper we give an in depth survey about Back-end of cloud services their concerns and the importance of privacy in cloud, Privacy Mechanism in cloud, Ways to Improve the Privacy in cloud, Hazards, Cloud Computing Issues and Challenges we discuss the need of cryptography and a survey of existing cryptographic algorithms. We discuss about the auditing and its classifications with respect to comparative study. In this paper analyzed various encryption schemes and auditing schemes with several existing algorithms which help in the improvement of cloud services.

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.

ABSTRACT: As cloud computing continues to play a pivotal role in data storage and processing, ensuring the security and integrity of transferred data remains a critical concern. This project introduces a novel approach for secure data transfer and detection leveraging the Counting Bloom Filter in cloud computing environments. The proposed system addresses the vulnerabilities associated with traditional data transfer methods by incorporating the Counting Bloom Filter, a probabilistic data structure. This technology aids in optimizing storage efficiency and enhances the accuracy of data detection, crucial for maintaining data integrity during transmission. The project focuses on these cure transfer of sensitive information within cloud computing environments, providing an added layer of protection against unauthorized access and potential data corruption. The Counting Bloom Filter is employed to detect anomalies and ensure the integrity of the transferred data, contributing to a robust and reliable cloud-based data transfer mechanism. Key objectives of the project include the implementation of advanced encryption techniques for secure data transfer, the integration of the Counting Bloom Filter for efficient data detection, and the development of a comprehensive system ensuring data integrity in the cloud. The project's innovation lies in its ability to enhance the security and reliability of data transfer in cloud computing, addressing the evolving challenges associated with data protection and privacy. In conclusion, the Secure Data Transfer and Detection from Counting Bloom Filter in Cloud Computing project represents a significant advancement in the realm of secure data transmission. By combining encryption methods with the unique capabilities of the Counting Bloom Filter, the project offers an effective solution for securing data during transfer, ensuring the integrity of information in cloud computing environments. Keywords:- Cloud computing, Data storage, Data processing, Data transfer, Security, Integrity, Counting Bloom Filter, Probabilistic, data structure, Storage efficiency, Data detection, Sensitive information, Encryption techniques, Unauthorized access, Data corruption, Anomaly detection, Data protection, Privacy, Secure data transfer, Cloud-based data transfer, System development, Data transmission.

Cloud Computing is a way to deal with fabricate the breaking point or incorporate capacities effectively without placing assets into new system, planning new staff, or approving new programming. They have various potential purposes of intrigue and various attempt applications and data are moving to open or half and half cloud. However, regarding some business-fundamental applications, the affiliations, especially considerable attempts, still wouldn't move them to cloud. The market gauge the Cloud Computing shared is as yet far behind the one expected. From the clients' perspective, Cloud Computing security concerns, especially data security and security confirmation issues, remain the basic inhibitor for gathering of Cloud Computing organizations. In this paper, we present a diagram on data security and security protection issues related with Cloud Computing over all periods of data life cycle. Firstly,, we moreover focus a related works and after that we show unpretentious components of Cloud Computing security issues, and a short time later data security and insurance affirmation issues, and a while later we display some present courses of action in cloud. Finally, we look at future work about data security and security affirmation issues in cloud. Keywords: cloud computing; security deployment; privacy protection infrastructure.

The popularity of cloud computing is increasing day by day. Everyone, knowingly or unknowingly, is using the services of cloud computing. Users are having very limited capability devices in terms of storage or processing, etc. To solve the storage issues, they use remote cloud storage for outsourcing their data that results in various benefits to users or reduces the burden of users. However, with these benefits, some security concerns need to be addressed that are confidentiality, integrity, and availability. Cloud data integrity means whether the user’s outsourced data is intact or not. Many researchers have proposed various schemes to verify cloud data integrity. Starting with some initial work in this area, this paper reviews the most recent existing data integrity schemes based on some identified characteristics. It also provides the future research directions that can be used as a guidemap for various researchers in cloud data integrity verification area.KeywordsData integrity verificationCloud computingCloud security issuesCloud data auditingOutsourcing dataCloud storageProvable data possessionProof of retrievability

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.

Cloud computing is the new bending curve in the line of Information Technology and computing paradigm. Cloud computing has simultaneously revolutionized business and government sectors by stretching its arms in every possible field, from not only to Information communication technology to medical advancements to a more diverse agriculture field which was untouched by technology for a decade. Cloud computing enlightens path for another dimension of computing which is expected to rise even more than mobile computing, i.e., Internet of Things (IOT) or internet of everything. As new dimensions are being added up to the cloud domain every day this gives a window to hackers and intruders to breach the doors. The security problem is amplified under cloud computing as it introduces new problem domains. One of the major problem domain identified is data security, where security of user’s data is the utmost priority. Providing privacy to the user and the data stored by the user is to be ensured by the cloud service provider. This paper aims at the security model for cloud computing which ensures the data security and integrity of user’s data stored in the cloud using cryptography.

Cloud computing is defined as the management and provision of resources, software, applications, and information as services over the internet. Numerous organizations are adopting cloud services because of the economy and technology changes. Over the past year, cloud computing has made life easier for other people or organizations by allowing people to have access to information from anywhere in the world through the internet. However, cloud computing introduces a series of security concerns, which data security is a major concern. Data security is basically linked with any security in the cloud. If the network or infrastructure security is compromised, the possibility there is a possibility of data being affected. Data security has three important principles that are Confidentiality, Integrity, and Availability (CIA) that needs to always be maintained. Understanding the security concerns in cloud computing is an important requirement for those who are planning to move to the cloud solution. Thus, this paper aims to investigate and develop a hybrid data security framework to mitigate data security challenges in the cloud, focusing on legal frameworks such as POPIA and GDPR. A survey was conducted to investigate which techniques are more effective in protecting data and the evaluation ensured that CIA triads are covered. The limitation on the existing techniques is that they address only one principle or two, but not all three at the same time. The best technique among the others will be used integrated when designing the proposed framework in order to address CIA. Having more than one security technique to address data security will improve the security in the cloud and will also bring more business to cloud service providers when customers see the security in data enhanced.

Cloud is the next generation platform that affords distributed computing environments and dynamic resource pools. Cloud computing is used to crack the daily computing problems providing a full time solution. But the problem related with cloud computing is the data security and data integrity over the Network. This paper is dealt with data security in the cloud environment using RSA digital signatures and robust reversible watermarking technique. In this research paper, we have to tried to increase the MSE and PSNR value of the Decrypted and De-watermarked image in order to prevent more distortion and degradation. In cloud, the cloud service provider or some other person may illegally try to hack customer's information. So, in order to avoid that, customer can encrypt their data by using their own encryption key and watermark their information at the user end. Furthermore, RSA algorithm is the most powerful encryption method used in internet security and Robust Reversible Watermarking technique works good in both lossy and lossless environment. So this combination may generate high PSNR value with minimum mean square error.

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.

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.