Enabling Efficient Deduplication and Secure Decentralized Public Auditing for Cloud Storage: A Redactable Blockchain Approach

<span lang="EN-US">Cloud Computing is the ability to improve the utility or train new human resources without investing in new infrastructure, or add capabilities to existence without the latest software licensing. It expanded the capabilities of Information Technology (IT). From the past few years, cloud computing has developed from a good business concept in the best rising sectors of the IT industry. But more information on individuals and companies was put in the cloud, and concerns began to think about how secure the cloud environment was. Despite cloud surrounding structures, enterprise users still do not want to expand their business in the cloud. Security reduces the growth of cloud computing and continues to spread the market with complexity with data privacy and data protection. The security of cloud computing has constantly been an significant aspect of improved quality of service from cloud service providers. Data storage in the cloud has a problem related to data security. However, cloud computing construct many new security challenges which have not been well examine. In order to ensure that the user's data in the cloud is secure, we have proposed an effective mechanism with a distinctive feature of data integrity and privacy. This paper focusing on problems relating to the cloud data storage techniques and security in virtual environment. We recommend a method for providing data storage and security in cloud using public key Cryptosystem, which uses the concept of the modified RSA algorithm to provide better security for the data stored in the cloud. </span>

In spite of the growing usage of smart mobile devices, the inherent restrictions like resource scarcity, mobility and frequent disconnections makes it difficult to exploit its full potential. Cloud computing simplifies the deployment of large-scale distributed systems and enables advanced computational power with improved storage capabilities. The evolution of Mobile Cloud Computing (MCC) exploits the services of Cloud Service Providers (CSP) by outsourcing the local data storage and computation to the remote servers and thereby relieving the overhead incurred by mobile clients for data storage and processing. In spite of the relief, the clients no longer have control over their outsourced data which demands the purpose of ensuring the data intactness maintained by the Cloud Storage Server (CSS). The resource constrained mobile devices act as a thin client for the cloud server access and hence the computation for ensuring the proof of correctness for secure data storage becomes an overhead with existing solutions. The proposed auditing protocol introduces a trusted third party auditor (TPA) who will be in charge of verifying the correctness of data stored at cloud storage on behalf of the user without the need for retrieving the entire data. The usage of Bilinear pairing and Merkle Hash Trees guarantees Blockless verification by TPA. The verification process in the proposed method reduces the auditing overhead at the mobile device using short signatures. The proposed auditing protocol saves the mobile client's computational resource, thereby achieving cost-effectiveness to gain trust in the Cloud Storage Service.

Data redundancy consumes huge storage space while setting up or employing cloud and fog storage. The dynamic cloud nature primarily focuses on the static environments which must be revised. Data deduplication solutions help minimize and control this issue by eradicating duplicate data from cloud storage systems. Since it might improve storage economy and security, data deduplication (DD) over encrypted data is a crucial problem in computing and storage systems. In this research, a novel approach to building secure deduplication systems across cloud and fog environments is developed. It uses MCDD and convergent cryptographic algorithms. The two most significant objectives of such systems are the focus of the suggested approach. Data redundancy must be minimized, but it also needs to be secured using a robust encryption method, which needs to be devised. The suggested approach is ideally suited for tasks like a user uploading new data to cloud storage or the fog. The proposed method might eliminate data redundancy by detecting redundancy at the block level. The testing results indicate that the recommended methodology can surpass a few cutting-edge techniques regarding computing effectiveness and security levels. The file is encrypted twice, once with the modified cryptographic model for deduplication (MCDD) and once with convergence encryption (CE).

Cloud storage relieves the user from the local management of software and hardware by enabling high quality on demand storage services to store their data in remote locations. Storing the data in remote locations not only reduces the management overheads but also eliminates the user’s physical control over data storage and data security. The loss of physical control over data brings out various security issues such as data loss, tampering of data, data modification. The primary issue is to ensure the correctness of data stored in remote locations which can be resolved by enabling public auditing for cloud storage services. In public auditing, not only the user but anyone can verify the data correctness. The introduction of third-party auditor, who works on behalf of cloud user to verify data integrity helps to reduce user computation resources and cost. The key prerequisite for the public auditing protocol is to support dynamic data operations as data in cloud are dynamic in nature. Cloud is a multiuser environment, so the auditing protocol must scale well to handle multiple auditing processes simultaneously. This paper aims at an extensive survey which mainly outlines the requirements for cloud public auditability and compares varied public auditing protocols.

Data deduplication is a valuable technique for compressing and minimizing data duplication during data transfers, especially in cloud environments. By eliminating redundant data, it optimizes transmission capacity and reduces memory usage. To ensure the integrity of sensitive data, encryption is applied throughout the deduplication process. The SHA algorithm is commonly used for storing text data during deduplication. It generates security bits by padding the text and computes a hash consisting of hexadecimal, string, and integer data. Hash-based deduplication involves hashing the entire file and treating the hash values of text data as unique identifiers. This allows clients to identify duplicate data within the cloud. The Proof-of-Work (PoW) algorithm is widely utilized in blockchain networks like Bitcoin and Ethereum. Its primary function is to verify transactions through a process called mining. Miners engage in competition to solve complex mathematical problems, and the first one to find a solution is granted the right to add a new block to the blockchain. PoW relies on cryptographic hashing, such as the SHA-256 hashing function, to validate and secure transactions. On the other hand, the Proof of Retrievability (PoR) algorithm finds application in cloud computing systems. It serves as a consensus mechanism, ensuring that cloud storage providers store and retrieve data accurately. PoR enables cloud providers to demonstrate to consumers that their files can be fully recovered. This algorithm incorporates cryptographic proofs that validate the integrity and availability of the stored data. In cloud storage, deduplication is often implemented using the Memory mapping technique (MPT). This allows multiple data owners to store the same data in a single copy, enhancing storage efficiency. To maintain data security, encryption is applied both before and during the deduplication process, ensuring that sensitive information remains protected. In summary, data deduplication is a powerful method for compressing data, minimizing duplication, and optimizing transmission capacity. With encryption techniques and hash-based identification, it provides secure and efficient deduplication in cloud environments, while memory deduplication and MPT support further enhance performance and storage efficiency.

Due to extensive coverage and domains of cloud computing-based architecture, most users saves and access highly similar data because of user habits and available resources. Supposing the data stored in the storage devices is of high duplication and similarity, the system administrator cannot guarantee that every node (peer) in the cloud computing system can maintain the best status for data integration. Moreover, when the number of nodes keeps increasing, the number of files will be multiplied, which results to not only the system administrator's heavy workload, but also the waste of hardware resources. Finally, the flexibility and quickness of cloud storage system is gone, and what left is a lot of duplicate and redundant data. Therefore, in order to avoid the system burden caused by duplicate data, we propose novel data center management architecture: Index Name Server (INS), which integrates de-duplication and access point selection optimization techniques to enhance the performance of the cloud storage system. With the attempt to attain load balancing, we use several specific INS parameters to dynamically monitor the parameters, like IP information and busy level index, to avoid the network congestion or the long waiting time during data transmission.

Cloud computing has empowered the individual user by providing seemingly unlimited storage space and availability and accessibility of data anytime and anywhere. Cloud service providers are able to maximize data storage space by incorporating data deduplication into cloud storage. Although data deduplication removes data redundancy and data replication, it also introduces major data privacy and security issues for the user. In this paper, a new privacy-preserving framework that addresses this issue is proposed. Our framework uses an efficient deduplication algorithm to divide a given file into smaller units. These units are then encrypted by the user using the combination of a secure hash function and a block encryption algorithm. An index tree of hash values of these units is also generated and encrypted using an asymmetric search encryption scheme by the user. This index tree will enable the cloud service provider to search through the index and return the requested units. We will show that our proposed framework will allow cloud service and storage providers to employ data deduplication techniques without giving them access to either the users' plaintexts or the users' decryption keys.

According to Cisco Global Cloud Index, cloud storage users will store 1.6 Gigabytes data per month by 2019, compared to 992 megabytes data per month in 2014. With this trend, it has been shown that more and more data will reside in cloud storage and it is expected to grow further. As cloud storage is becoming an option for users for keeping their data online, it comes with security concerns for protecting data from threats. This thesis addresses the need to investigate the security factors that will enable efficient security protection for data in cloud storage and the relationships that exist between the different security factors. Consequently, this research has developed a conceptual framework that supports security in cloud storage. The main contribution of this research is the development of a Cloud Storage Security Framework (CSSF) to support an integrative approach to understanding and evaluating security in cloud storage. The framework enables understanding of the makeup of security in cloud storage and measures the understanding of security in cloud storage. Drawing upon established theories and prior research findings, the framework indicates that security in cloud storage can be determined by nine factors: (1) security policies implementation in cloud storage, security measure that relates to (2) protecting the data accessed in cloud storage; (3) modifications of data stored; (4) accessibility of data stored in cloud storage; (5) non-repudiation to the data stored; (6) authenticity of the original data; (7) reliability of the cloud storage services; (8) accountability of service provision; and (9) auditability of the data accessed and stored in cloud storage. An example of CSSF application has been demonstrated through the development of a measuring instrument called Security Rating Score (SecRaS) and through a series of experiments, SecRaS has been validated and used in a research scenario. The instrument consists of several items generated using goal-question-metric approach. These potential items were evaluated by a series of experiments; the security experts assessed using content validity ratio while the security practitioners took part in the validation study. The validation study completed two experiments that look into the correlation analyses and internal reliability. SecRaS instrument was later applied in a research scenario; the validated instrument was distributed and a number of 218 usable responses were received. Using structural equation modelling, the data has revealed a good fit of the measurement analyses and structural model. The key findings were as follow: the relationships between factors were found to have both direct and indirect effects in the result. While establishing the relationship(s) among the factors, the structural model proposes three types of causal relationships in terms of how the security implementation in cloud storage could be affected by the security factors. This thesis presents a detailed discussion of the CSSF development, confirmation, and application in a research scenario. For security managers, CSSF offers a new paradigm on how stakeholders can make cloud storage security implementation successful in some depth. For security practitioners, the CSSF enables deconstruction of the concept of security in cloud storage into smaller, conceptually distinct and manageable factors to guide the design of security in cloud storage. For researchers, the CSSF provides a common framework in which to conceptualise their research and make it easier to see how the security factors fit into the larger picture.

Organizations worldwide commonly utilize cloud infrastructure to manage large volumes of data, making the optimization of storage crucial for enhancing cloud performance. One effective optimization technique is data deduplication, which identifies duplicate objects and ensures that only one copy of unique data is stored in the cloud. While several deduplication schemes currently exist, there is a pressing need to improve efficiency in cloud storage through innovative approaches. In this paper, we propose a new system model designed to facilitate an efficient deduplication process. Our algorithm, called deduplication in cloud infrastructure (DCI), offers a systematic and effective method for handling deduplication challenges related to redundant data storage. DCI focuses on hash generation, metadata comparison, and pointer-based deduplication, providing a comprehensive strategy for optimizing cloud storage resources and minimizing duplication. This ultimately enhances both the efficiency and cost-effectiveness of cloud-based data management. A simulation study using CloudSim and the Hadoop distributed file system (HDFS) simulator demonstrates that the proposed deduplication method is effective. Experimental results show that our algorithm outperforms many existing solutions, achieving the highest deduplication ratio of 6.7 and saving 85.09% of storage space due to its efficient deduplication approach. The proposed system can be used in cloud infrastructures for efficiency.

The recent developments in mobile applications have met every need of the user. In spite of increasing usage, the smart mobile system face restrictions like resource scarcity, mobility and frequent disconnections. The emerging Mobile Cloud Computing (MCC) infrastructure exploits the services of Cloud Service Providers (CSP) by gathering the local data storage and computation to remote servers and thereby relieving the overhead incurred by mobile clients. There is a wide range of applications in MCC like m-Learning, m-Healthcare, etc. Though the restrictions are relaxed, the clients no longer have control over the privacy of outsourced data. A safe and secure remote access to highly sensitive private data like e-Health records has received the focus of research. It needs to ensure the integrity of outsourced health data along with its privacy preserved. The resource constrained mobile devices act as a thin client for the cloud server access and hence the computation for ensuring the proof of correctness for secure data storage proposed by existing solutions becomes an overhead. The proposed Provable Dynamic Data Auditing Protocol (PD-DAP) involves a trusted Third Party Auditor (TPA) who is in charge of blockless verification of data without retrieving the private health data. The usage of bilinear pairing and Merkle Hash Trees guarantees blockless verification by TPA. Also the proposed PD-DAP supports secure dynamic operations by the mobile user with the help of TPA. Hence, it saves the mobile user’s computational resource, thereby achieving cost-effectiveness to gain trust in the Cloud Storage Server (CSS).

Public auditing schemes for cloud storage systems have been extensively explored with the increasing importance of data integrity. A third-party auditor (TPA) is introduced in public auditing schemes to verify the integrity of outsourced data on behalf of users. To resist malicious TPAs, many blockchain-based public verification schemes have been proposed. However, existing auditing schemes rely on a centralized TPA, and they are vulnerable to tempting auditors who may collude with malicious blockchain miners to produce biased auditing results. In this article, we propose a blockchain-based decentralized public auditing (BDPA) scheme by utilizing a decentralized blockchain network to undertake the responsibility of a centralized TPA, and also mitigate the influence of tempting auditors and malicious blockchain miners by taking the concept of decentralized autonomous organization (DAO). A detailed security analysis shows that BDPA can preserve data integrity against tempting auditors and malicious blockchain miners. A comprehensive performance evaluation demonstrates that BDPA is feasible and scalable.

Cloud storage enables users to remotely store their data and benefit of the demand high quality cloud applications without the difficulty of local hardware and software management. Though the benefits are clear, such a service is also reliable to the users’ physical possession of their outsourced data, which inevitably poses new security risks towards the recovery of the data in cloud. In order to address this new problem and further achieve a secure and useful cloud storage service, we propose in this study a flexible distributed storage integrity mechanism, utilizing the homomorphic token and distributed data. The proposed design allows users to check the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, efficiency, but also simultaneously to access data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design future supports secure and efficient dynamic operations on outsourced data, including block modification, update, deletion and append. The proposed scheme is highly efficient and secure against Byzantine failure, malicious data modification attack and even server colluding attacks.

In cloud storage the data clients can remotely store their data and use on-demand high- quality applications. Data outsourcing users are reassured from the trouble of data storage and maintenance when users put their data in huge size on the cloud, the data integrity protection is a challenging one which enabling public audit for cloud data storage security. Users can ask an external inspection of third party to check the integrity of the out sourced data. However, in such a scheme, the malicious cloud might still forge valid authenticators later than the key-revelation time period if it obtains the current secret key of Data Client. In this paper, propose a prototype named Robust Key Revelation of public auditing for secure cloud storage, in which the security of cloud storage auditing not only earlier than but also later than the key revelation can be preserved. Formalized the definition and the security model of this new kind of cloud storage auditing and design a concrete scheme. In this proposed prototype, the key revelation in one-time period doesn’t affect the security of cloud storage auditing in other time periods. The accurate security proof and the experimental results demonstrate that this proposed prototype achieves desirable security and efficiency with the time intervals. Keywords: Secure Cloud Storage, Robust Key Revelation, Security, Data Client, and Public Auditing.

Cloud computing provides a scalable platform for large amount of data and processes that work on various applications and services by means of on-demand service. The storage services offered by clouds have become a new profit growth by providing a comparable cheaper, scalable, location-independent platform for managing users’ data. The client uses the cloud storage and enjoys the high end applications and services from a shared group of configurable computing resources using cloud services. It reduces the difficulty of local data storage and maintenance. But it gives severe security issues toward users’ outsourced data. Data Redundancy promotes the data reliability in Cloud Storage. At the same time, it increases storage space, Bandwidth and Security threats due to some server vulnerability. Data Deduplication helps to improve storage utilization. Backup is also less which means less Hardware and Backup media. But it has lots of security issues. Data reliability is a very risky issue in a Deduplication storage system because there is single copy for each file stored in the server which is shared by all the data owners. If such a shared file/chunk was missing, large amount of data becomes unreachable. The main aim of this work is to implement Deduplication System without sacrificing Security in cloud storage. It combines both Deduplication and convergent key cryptography with reduced overhead.

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.