34,626 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
XYZ Privacy
Future autonomous vehicles will generate, collect, aggregate and consume
significant volumes of data as key gateway devices in emerging Internet of
Things scenarios. While vehicles are widely accepted as one of the most
challenging mobility contexts in which to achieve effective data
communications, less attention has been paid to the privacy of data emerging
from these vehicles. The quality and usability of such privatized data will lie
at the heart of future safe and efficient transportation solutions.
In this paper, we present the XYZ Privacy mechanism. XYZ Privacy is to our
knowledge the first such mechanism that enables data creators to submit
multiple contradictory responses to a query, whilst preserving utility measured
as the absolute error from the actual original data. The functionalities are
achieved in both a scalable and secure fashion. For instance, individual
location data can be obfuscated while preserving utility, thereby enabling the
scheme to transparently integrate with existing systems (e.g. Waze). A new
cryptographic primitive Function Secret Sharing is used to achieve
non-attributable writes and we show an order of magnitude improvement from the
default implementation.Comment: arXiv admin note: text overlap with arXiv:1708.0188
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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