Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing
Cong Wang,Qian Wang,Kui Ren,Wenjing Lou +3 more
- pp 525-533
TLDR
This paper utilize and uniquely combine the public key based homomorphic authenticator with random masking to achieve the privacy-preserving public cloud data auditing system, which meets all above requirements.Abstract:
Cloud Computing is the long dreamed vision of computing as a utility, where users can remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. By data outsourcing, users can be relieved from the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the possibly large size of outsourced data makes the data integrity protection in Cloud Computing a very challenging and potentially formidable task, especially for users with constrained computing resources and capabilities. Thus, enabling public auditability for cloud data storage security is of critical importance so that users can resort to an external audit party to check the integrity of outsourced data when needed. To securely introduce an effective third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should bring in no new vulnerabilities towards user data privacy. In this paper, we utilize and uniquely combine the public key based homomorphic authenticator with random masking to achieve the privacy-preserving public cloud data auditing system, which meets all above requirements. To support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis shows the proposed schemes are provably secure and highly efficient.read more
Citations
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Proceedings ArticleDOI
Efficient Integrity Auditing for Shared Data in the Cloud with Secure User Revocation
TL;DR: This paper proposes a novel public auditing scheme for the integrity of shared data with efficient and collusion-resistant user revocation utilizing the concept of Shamir secret sharing and demonstrates that the proposed scheme is provably secure and highly efficient.
Journal ArticleDOI
Performance Evaluation of Min-Min and Max-Min Algorithms for Job Scheduling in Federated Cloud
TL;DR: This study investigates the performance of min-min and minmax scheduling algorithms using CloudSim software to understand its implications on customers’ applications or Cloud deployed systems.
SUODY-Preserving Privacy in Sharing Data with Multi-Vendor for Dynamic Groups
TL;DR: This paper proposes a privacy preserved multi owner data sharing scheme, named Suody, taking maximum advantage of group signature to construct homomorphic authenticators, signed receipts and dynamic broadcast encryption techniques, so that a user in the cloud can share the data with others using withheld authorship.
Journal ArticleDOI
Integrity Audit of Shared Cloud Data with Identity Tracking
TL;DR: In this scheme, the user sends the encrypted data to the cloud and the data tag to the Rights Distribution Center (RDC) by using data blindness technology and the security of the scheme is proved through provable security theory.
Journal ArticleDOI
A Privacy-Preserving and Untraceable Group Data Sharing Scheme in Cloud Computing
TL;DR: Wang et al. as mentioned in this paper proposed a privacy-preserving and untraceable scheme to support multiple users in sharing data in cloud computing, where group members and a proxy use the key exchange phase to obtain keys and resist multiparty collusion if necessary.
References
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