RSA-based dynamic public audit service for integrity verification of data storage in cloud computing using Sobol sequence

Data outsourcing through cloud storage enables the users to share on-demand resources with cost effective IT services but several security issues arise like confidentiality, integrity and authentication. Each of them plays an important role in the successful achievement of the other. In cloud computing data integrity assurance is one of the major challenges because the user has no control over the security mechanism to protect the data. Data integrity insures that data received are the same as data stored. It is a result of data security but data integrity refers to validity and accuracy of data rather than protect the data. Data security refers to protection of data against unauthorized access, modification or corruption and it is necessary to ensure data integrity. This paper proposed a new approach using Matrix Dialing Method in block level to enhance the performance of both data integrity and data security without using Third Party Auditor (TPA). In this approach, the data are partitioned into number of blocks and each block converted into a square matrix. Determinant factor of each matrix is generated dynamically to ensure data integrity. This model also implements a combination of AES algorithm and SHA-1 algorithm for digital signature generation. Data coloring on digital signature is applied to ensure data security with better performance. The performance analysis using cloud simulator shows that the proposed scheme is highly efficient and secure as it overcomes the limitations of previous approaches of data security using encryption and decryption algorithms and data integrity assurance using TPA due to server computation time and accuracy.

Cloud computing is a promising technology that provides several advantages to services provider, developers and customers with respect to litheness, scalability at a lower cost. With these technical and cost cutting advantages, several data owners outsourced their data to cloud storage where the data is not only stored but also distribute amongst several users. The promising Cloud computing technology provides convenient access to their data, computing resources on pay-as-you-use basis. This paradigm gives an option of remotely storing their data so as to enjoy powerful application, on-demand network access to computing resources. With these benefits user can decrease the load on local data storage space and reduce the maintenance cost. The main challenging task for the user is to protect the data from unauthorized access, data privacy preservation, modification and deletion of original data. Several methods were used to verify the integrity of outsourced data in cloud storage. This paper presents the Data Privacy preservation model using Third Party Auditing (TPA) which helps to audits the integrity of the data without demanding the local copy of data, and any additional burden. Our system model also uses bilinear aggregate signatures so that TPA can handle multiple client auditing requests concurrently. We conduct the Experiment with diverse methods and the compare the performance of the each method. The results show that the proposed method is secure and more efficient as compare to the existing methods in terms of performances.

Cloud storage is a mode of online storage in which data are stored on multiple virtual servers usually hosted by third parties. Cloud service providers manage and operate data storage as services. The major concern in cloud storage is the integrity of outsourced data. Many public auditing schemes which authorize the third party auditor (TPA) to check the integrity of outsourced data have been proposed. However, most of them are based on traditional public key cryptosystems. This paper proposes an efficient certificateless public auditing Scheme (CL‐PAS) in cloud storage. In the process of challenge and auditing, CL‐PAS ensures that malicious cloud servers cannot forge auditing evidences to deceive TPA to pass the verification, and prevents curious TPA from recovering original data from auditing evidences. So it strengthens privacy preserving. Security analysis shows that CL‐PAS scheme meets the predetermined security requirements. The simulation and performance analysis results show that, compared with similar schemes, CL‐PAS scheme has the higher efficiency.

<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>

Data storage is an important application of cloud computing, where clients can remotely store their data into the cloud. By uploading their data into the cloud, clients can be relieved from the burden of local data storage and maintenance. This new paradigm of data storage service also introduces new security challenges. One of these risks that can attack the cloud computing is the integrity of the data stored in the cloud. In order to overcome the threat of integrity of data, the client must be able to use the assistance of a Third Party Auditor (TPA), in such a way that the TPA verifies the integrity of data stored in cloud with the client's public key on the behalf of the client. The existing schemes with single verifier (TPA) may not scale well for this purpose. In this paper, we propose An Efficient Distributed Verification Protocol (EDVP) to verify the integrity of data in a distributed manner with support of multiple verifiers (Multiple TPAs) instead of single Verifier (TPA). Through the extensive security, performance and experimental results, we show that our scheme is more efficient than single verifier based scheme.

Using cloud data clients may transfer data from their computer systems to cloud servers. Hence, user will not have any burden of maintenance and also he gets high quality data storage services. Many security issues are concerned with cloud storage. Cloud service providers or storage servers are not completely trustworthy. The user is concerned about the information stored on cloud are in place or not turns. This paper is based on homomorphic hash algorithm. Further this supports dynamic operations such as insert, update, delete and modify at block level, for data dynamics Merkle Hash Tree is used which helps to find the location of each dynamic operation. Third party auditor checks the user's data for correctness and gives the accuracy of the data that is stored in cloud server. The communication and computation overhead are reduced. Deduplication technique is used to check whether the file that user need to store in cloud storage is already exist at cloud server or not. This framework is effective and secure against replace attack launch by malicious server.

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.

The utilization of "cloud storage services (CSS)", empowering people to store their data in cloud and avoid from maintenance cost and local data storage. Various data integrity auditing (DIA) frameworks are carried out to ensure the quality of data stored in cloud. Mostly, if not all, of current plans, a client requires to utilize his private key (PK) to generate information authenticators for knowing the DIA. Subsequently, the client needs to have hardware token to store his PK and retain a secret phrase to actuate this PK. In this hardware token is misplaced or password is forgotten, the greater part of existing DIA plans would be not able to work. To overcome this challenge, this research work suggests another DIA without "private key storage (PKS)"plan. This research work utilizes biometric information as client's fuzzy private key (FPK) to evade utilizing hardware token. In the meantime, the plan might in any case viably complete the DIA. This research work uses a direct sketch with coding and mistake correction procedures to affirm client identity. Also, this research work plan another mark conspire that helps block less. Verifiability, yet in addition is viable with linear sketch Keywords– Data integrity auditing (DIA), Cloud Computing, Block less Verifiability, fuzzy biometric data, secure cloud storage (SCS), key exposure resilience (KER), Third Party Auditor (TPA), cloud audit server (CAS), cloud storage server (CSS), Provable Data Possession (PDP)

The remote data integrity auditing technology can guarantee the integrity of outsourced data in clouds. Users can periodically run an integrity auditing protocol by interacting with cloud server, to verify the latest status of outsourced data. Integrity auditing requires user to take massive time-consuming computations, which would not be affordable by weak devices. In this paper, we propose a privacy-preserving TPA-aided remote data integrity auditing scheme based on Li et al.’s data integrity auditing scheme without bilinear pairings, where a third party auditor (TPA) is employed to perform integrity auditing on outsourced data for users. The privacy of outsourced data can be guaranteed against TPA in the sense that TPA could not infer its contents from the returned proofs in the integrity auditing phase. Our construction is as efficient as Li et al.’s scheme, that is, each procedure takes the same time-consuming operations in both schemes, and our solution does not increase the sizes of processed data, challenge and proof.

Public auditing for cloud storage is of critical importance as the users relies on semi-trusted cloud storage service for data sharing which does not guarantee/assure the integrity of the data being stored. With public auditing of clouds, users resort to a third party auditor (TPA) who verify and assure the internal consistency/lack of corruption of their data in cloud storage services. Despite the good work previously done by researchers in auditing while preserving privacy, still available mechanisms do not efficiently conceal users' privacy from TPA during sharing of data and yet supporting data and group dynamics. In this paper, we propose privacypreserving auditing scheme that exploits the ring signature to calculate verifications needed to audit data integrity.In this proposed approach, the identities of the user are kept private from public verifier and dynamic groups are supported -that is a new user can be added into the group and an existing group member can be revoked during data sharing.

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.

Cloud data storage is a model of data storage where data in its digital form is stored in logical pools across the physical storage which is distributed across multiple servers usually in diverse locations. The full physical environment is owned and managed by an organization called Cloud Service Provider (CSP). In this type of storage, the data is distributed and owned by third party, and there is risk of unauthorized access. This makes security, reliability, confidentiality and privacy of data more important when storage in cloud is thought of. Although there are methods available for providing security, much work is not done with emphasis on dynamic nature of the data. Hence securing the data while updating becomes important. In this paper, a method that ensures confidentiality of data stored in cloud using homomorphic encryption is presented. The paper also provides a technique to ensure confidentiality during data updates in cloud. The presented method includes byte level automorphism for ensuring data integrity and confidentiality. The tabulated experimental results show that the proposed method provides more secure frame work for ensuring confidentiality and integrity of data in cloud.

Cloud computing is an internet based model which allows the user all the "services on demand".The services provided by cloud are infrastructure, software and platform.Cloud Computing has great potential of providing robust computational power to the society at reduced cost.Despite the tremendous benefits, security is the primary obstacle that prevents the wide adoption of this promising computing model, especially for customers when their confidential data are consumed and produced during the computation.Wang proposed enabling public audit ability and data dynamics for storage security in cloud computing which provides data integrity and dynamic operation but cannot assure confidentiality.Here in this scheme we are providing a new method which provide confidentiality and also manage the storage space in cloud server.In this we are providing confidentiality by using cryptographic algorithm and storage space is managed by using complete binary tree by arranging all the files by their size and checking the integrity using TPA(third party auditor).Thus providing integrity, memory management as well as confidentiality in cloud computing.

Along with the widespread interest in cloud computing, there are still concerns that hinder the proliferation and the adoption of cloud services. One of the main concerns is data security in cloud storage environments. Numerous research problems belonging to cloud storage security have been studied intensively before. However, addressing the three dimensions of outsourced data security (i.e., confidentiality, availability, and integrity) as a cloud service is still a challenge in cloud storage. As there is always a tradeoff between maintaining security and obtaining efficiency, it is difficult but nevertheless essential to explore how to efficiently address security challenges over dynamic cloud data. This paper proposes an integrated security model for data storage in the cloud that provides authentication, access control, auditing and data management services. A strong authentication sub-system that is based on the traditional password and the user keystroke dynamics is presented. A dynamic access control system is proposed to ensure data confidentiality in cloud computing. A public auditing system is proposed to delegate the integrity verification of outsourced data in the cloud storage to a third party auditor while maintaining the data privacy. Experimental results demonstrate the effectiveness and efficiency of the proposed model.

Cryptanalysis of an integrity checking scheme for cloud data sharing