6,911 research outputs found
Prochlo: Strong Privacy for Analytics in the Crowd
The large-scale monitoring of computer users' software activities has become
commonplace, e.g., for application telemetry, error reporting, or demographic
profiling. This paper describes a principled systems architecture---Encode,
Shuffle, Analyze (ESA)---for performing such monitoring with high utility while
also protecting user privacy. The ESA design, and its Prochlo implementation,
are informed by our practical experiences with an existing, large deployment of
privacy-preserving software monitoring.
(cont.; see the paper
Secret Sharing for Cloud Data Security
Cloud computing helps reduce costs, increase business agility and deploy
solutions with a high return on investment for many types of applications.
However, data security is of premium importance to many users and often
restrains their adoption of cloud technologies. Various approaches, i.e., data
encryption, anonymization, replication and verification, help enforce different
facets of data security. Secret sharing is a particularly interesting
cryptographic technique. Its most advanced variants indeed simultaneously
enforce data privacy, availability and integrity, while allowing computation on
encrypted data. The aim of this paper is thus to wholly survey secret sharing
schemes with respect to data security, data access and costs in the
pay-as-you-go paradigm
A secure data outsourcing scheme based on Asmuth – Bloom secret sharing
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Data outsourcing is an emerging paradigm for data management in which a database is provided as a service by third-party service providers. One of the major benefits of offering database as a service is to provide organisations, which are unable to purchase expensive hardware and software to host their databases, with efficient data storage accessible online at a cheap rate. Despite that, several issues of data confidentiality, integrity, availability and efficient indexing of users’ queries at the server side have to be addressed in the data outsourcing paradigm. Service providers have to guarantee that their clients’ data are secured against internal (insider) and external attacks. This paper briefly analyses the existing indexing schemes in data outsourcing and highlights their advantages and disadvantages. Then, this paper proposes a secure data outsourcing scheme based on Asmuth–Bloom secret sharing which tries to address the issues in data outsourcing such as data confidentiality, availability and order preservation for efficient indexing
A threshold secure data sharing scheme for federated clouds
Cloud computing allows users to view computing in a new direction, as it uses
the existing technologies to provide better IT services at low-cost. To offer
high QOS to customers according SLA, cloud services broker or cloud service
provider uses individual cloud providers that work collaboratively to form a
federation of clouds. It is required in applications like Real-time online
interactive applications, weather research and forecasting etc., in which the
data and applications are complex and distributed. In these applications secret
data should be shared, so secure data sharing mechanism is required in
Federated clouds to reduce the risk of data intrusion, the loss of service
availability and to ensure data integrity. So In this paper we have proposed
zero knowledge data sharing scheme where Trusted Cloud Authority (TCA) will
control federated clouds for data sharing where the secret to be exchanged for
computation is encrypted and retrieved by individual cloud at the end. Our
scheme is based on the difficulty of solving the Discrete Logarithm problem
(DLOG) in a finite abelian group of large prime order which is NP-Hard. So our
proposed scheme provides data integrity in transit, data availability when one
of host providers are not available during the computation.Comment: 8 pages, 3 Figures, International Journal of Research in Computer
Science 2012. arXiv admin note: text overlap with arXiv:1003.3920 by other
author
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