A Privacy-Preserving TPA-aided Remote Data Integrity Auditing Scheme in Clouds

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.

A secure and scalable data integrity auditing scheme based on hyperledger fabric

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.

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.

Provable data deletion from efficient data integrity auditing and insertion in cloud storage

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.

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.

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)

Providing security to the stored data on the cloud is one of the important challenges in cloud computing. Encrypted data which is stored on the cloud may be viewed or modified by the cloud service provider. To overcome this problem many techniques have been developed but, those cannot guarantee accurately about the security of the stored data. These modifications of the data by the service provider or by others should also be known to the data owner. For such purpose, data tagging technique can be used to audit the data. Auditing is done by using Third Party Auditor (TPA). TPA stores data information of the data owner and challenges to the cloud server, depending upon the data owner request. With the help of such mechanism, TPA can convince both, data owner and cloud server.

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.

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources. User’s data is stored in large database. The stored data can be accessed and modified by the clients over the Internet. The data is monitored by the Third Party Auditor (TPA) on behalf of the client. Therefore, integrity is lacked by the data stored on the servers. The data integrity is ensured by the cloud services that provide trust to the privacy of users. Aiming at the urgent problem of network data security in cloud computing operations, this paper proposed a security situation assessment system to grasp the security situation in real time. A set of cloud computing network data storage security is proposed. Through this model, the extraction of network data storage security situation elements, the design of network data storage security situation assessment scheme and the calculation method of network data storage security situation value are completed. The experimental results show the error of the predicted value obtained by the network data storage security situation assessment system. The effectiveness of the system model and the superiority of the improved algorithm is verified by the experimental results. This paper uses the cloud model to predict the cloud computing network security situation. On the other hand, the security situation value obtained by the situation assessment process can be used directly without training the original situation value. Performance improvement by the proposed technique over existing technique is seen and it is observe that the proposed technique is 23% and 34% better than the existing techniques.

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).

Cloud computing is the next phase in the Internet's evolution, providing the means through which computing power, computing infrastructure, applications, business processes can be delivered to businesses and individual as a service wherever and whenever they need. Businesses who use cloud service providers (CSP) tend to have service level agreements (SLA) that act as contract and define the level of expected service from the CSP, including availability, performance and security. Recent research suggests the use of third party auditors (TPA) as a mean to monitor CSPs. This paper shows how CSP may deceit the SLA to reduce their cost and become more competitive, while avoiding detection by TPAs. The paper presents a crowdsourced TPA model to monitor the CSPs and consequently detect any deception.

Computing in the cloud is one of the platforms that may be used to provide distributed computing resources. Supplying and managing cloud resources most effectively is referred to as resource management. A recent development in technology known as fog computing is an example of an expanded and dispersed infrastructure. This architecture maintains application processes between end devices and the network edge to provide more dependable and efficient services. These services include remote data storage, allowing customers to access their data from a distant location. Providing remote storage service is an advantageous function offered by cloud suppliers. On the other hand, the data stored in the cloud is geographically dispersed and kept in various data centers, significantly increasing the risk to users' privacy and security. One of the problems that might arise with privacy is when many data centers store the same information. Many cloud service providers check their customers' data using a Third-Party Auditor (TPA) to address concerns about client privacy and data integrity. Currently, most trusted TPAs only have one validator, making it impossible to expand the data integrity across several data centers. The various verifiers used by TPAs have been reduced in number in response to Man in the Cloud (MiTC) attacks. As a result, they cannot check and authenticate the integrity of data stored in several data centers. A unique Peer to Peer (P2P) authentication protocol with Certificate Authority (CA) and Data Storage Protocol is presented as a solution to the problem that has been outlined above to check for and go around any issues that may arise (DSP). The efficiency of the proposed protocol is demonstrated by the incorporation of TPAs and Certificate Authorities. The proposed protocol has been tested with a single user and a single storage server, as well as multiple storage servers in ownCloud with one backup server, two storage servers, three clients, and two TPAs. The NoSQL server in an organization's cloud is set up to save data to storage servers in the appropriate format. The Amanda backup server is used to back up the mirror copy of the stored data on the storage servers. Automated Validation of Internet Security Protocols with Data Fusion and Applications, or AVISPA for short, is a technology that may be used to verify data stored in the cloud. The findings make it abundantly evident that the suggested protocol is strong enough to guarantee the authenticity of data kept in several data centers.

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.