Availability Of Outsourced Data Research Articles

Dynamic Multiple-Replica Provable Data Possession in Cloud Storage System

In cloud storage scenarios, data security has received considerably more attention than before. To ensure the reliability and availability of outsourced data and improve disaster resilience and data recovery ability, important data files possessed by users must be stored on multiple cloud service providers (CSPs). However, we know that CSP is invariably not reliable. In this situation, to verify the integrity of replica files stored by users on multiple CSPs simultaneously, a new dynamic multiple-replica provable data possession (DMR-PDP) scheme is proposed. In addition, due to the importance of the tag set, we utilize vector dot products instead of using the modular power calculation in the traditional PDP scheme, which greatly reduces the calculation time and storage space usage. Moreover, a novel dynamic data structure, the divided address-version mapping table (DAVMT), is presented and used to solve the problem of data dynamic operation. A practical experiment validates the effectiveness of our proposed scheme in the end.

Auditing a Cloud Provider’s Compliance With Data Backup Requirements: A Game Theoretical Analysis

The new developments in cloud computing have introduced significant security challenges to guarantee the confidentiality, integrity, and availability of outsourced data. A service level agreement (SLA) is usually signed between the cloud provider (CP) and the customer. For redundancy purposes, it is important to verify the CP’s compliance with data backup requirements in the SLA. There exist a number of security mechanisms to check the integrity and availability of outsourced data. This task can be performed by the customer or be delegated to an independent entity that we will refer to as the verifier. However, checking the availability of data introduces extra costs, which can discourage the customer of performing data verification too often. The interaction between the verifier and the CP can be captured using game theory in order to find an optimal data verification strategy. In this paper, we formulate this problem as a two player non-cooperative game. We consider the case in which each type of data is replicated a number of times, which can depend on a set of parameters including, among others, its size and sensitivity. We analyze the strategies of the CP and the verifier at the Nash equilibrium and derive the expected behavior of both the players. Finally, we validate our model numerically on a case study and explain how we evaluate the parameters in the model.

Rating cloud storage service by collaborative remote data checking

Cloud storage is a flexible platform for data outsourcing service. In such schemes, users no longer have the physical control of their data. As a result, the reliability of the cloud storage service is the major concern of users. Existing approaches evaluate the cloud storage provider CSP from users' feedback, which are subjective and often biased. In this paper, we propose a new rating algorithm to assess the credibility of CSPs. Our solution is based on technical evidence, e.g., results of the data possession checking, which is a useful approach to ensure the integrity and availability of outsourced data in the cloud. Our approach aggregates the collaborative provable data possession results from the community of clients to achieve high coverage. Meanwhile, we introduce a new reputation-based solution to detect malicious clients based on public verification, and adjust the trust value of such clients. We prototyped our approach and analysed the scheme thoroughly. The results demonstrated that the proposed method is efficient, secure, and has the distinguishing property that supports collaborative verification among composite cloud storage frameworks.

Secure and Efficient Audit Service Outsourcing for Data Integrity in Clouds

Cloud-based outsourced storage relieves the client’s load for storage management and maintenance by providing a comparably low-cost, scalable, location-independent platform. Though, the information that clients no longer have physical control of data specifies that they are facing a potentially formidable risk for missing or corrupted data. To avoid the security risks, inspection services are serious to ensure the integrity and availability of outsourced data and to achieve digital forensics and reliability on cloud computing. Provable data possession (PDP), which is a cryptographic method for validating the reliability of data without retrieving it at an untrusted server, can be used to realize audit services. In this project, profiting from the interactive zero-knowledge proof system, the construction of an interactive PDP protocol to prevent the fraudulence of prover (soundness property) and the leakage of verified data (zero knowledge property).To prove that our construction holds these properties based on the computation Diffie–Hellman assumption and the rewindable black-box knowledge extractor. An efficient mechanism on probabilistic queries and periodic verification is proposed to reduce the audit costs per verification and implement abnormal detection timely. Also, we present an efficient method for choosing an optimal parameter value to reduce computational overheads of cloud audit services.

Efficient audit service outsourcing for data integrity in clouds

Cloud-based outsourced storage relieves the client's burden for storage management and maintenance by providing a comparably low-cost, scalable, location-independent platform. However, the fact that clients no longer have physical possession of data indicates that they are facing a potentially formidable risk for missing or corrupted data. To avoid the security risks, audit services are critical to ensure the integrity and availability of outsourced data and to achieve digital forensics and credibility on cloud computing. Provable data possession (PDP), which is a cryptographic technique for verifying the integrity of data without retrieving it at an untrusted server, can be used to realize audit services.In this paper, profiting from the interactive zero-knowledge proof system, we address the construction of an interactive PDP protocol to prevent the fraudulence of prover (soundness property) and the leakage of verified data (zero-knowledge property). We prove that our construction holds these properties based on the computation Diffie–Hellman assumption and the rewindable black-box knowledge extractor. We also propose an efficient mechanism with respect to probabilistic queries and periodic verification to reduce the audit costs per verification and implement abnormal detection timely. In addition, we present an efficient method for selecting an optimal parameter value to minimize computational overheads of cloud audit services. Our experimental results demonstrate the effectiveness of our approach.