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Open AccessProceedings ArticleDOI

Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing

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.

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Citations
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Proceedings ArticleDOI

ALook: adaptive lookup for GPGPU acceleration

TL;DR: An adaptive look-up based approach, called ALook, which uses a dynamic update policy to maintain a set of recently used operations in associative memory and improves the GPU performance by 2.0X as compared to state-of-the-art computational reuse methods for the same level of output error.
Proceedings ArticleDOI

Secure Third Party Auditor for Ensuring Data Integrity in Cloud Storage

TL;DR: This work offers a new TPA model that differs from previous models and overcomes the above-mentioned issues, and includes many security features such as secure and efficient use of the TPA for correct data storage with supporting data dynamics.
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SSE: A Secure Searchable Encryption Scheme for Urban Sensing and Querying:

TL;DR: A secure searchable encryption scheme, named SSE, for urban sensing and querying, which constructs a secure hidden vector encryption-(HVE-) based rang query predicate and ensures data confidentiality and integrity and source authentication are preserved.
Journal ArticleDOI

Preserving identity privacy on multi-owner cloud data during public verification

TL;DR: This paper designs a novel public verification scheme to audit the integrity of multi-owner data stored in the cloud with a very small communication cost compared with the size of the entire data.
Journal ArticleDOI

Blockchain-Based Transparent Integrity Auditing and Encrypted Deduplication for Cloud Storage

TL;DR: Wang et al. as mentioned in this paper introduced a concept of transparent integrity auditing and proposed a concrete scheme based on the blockchain, which goes one step beyond existing public auditing schemes, since the auditing does not rely on third-party auditors while freeing users from heavy communication costs on auditing the data integrity.
References
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Journal Article

Above the Clouds: A Berkeley View of Cloud Computing

TL;DR: This work focuses on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SAAS Users, and uses the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public.
Book ChapterDOI

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Posted Content

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Journal ArticleDOI

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