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Authentication of Data on Devices

Authors: Ashish Kundu;

Authentication of Data on Devices

Abstract

Use of smart-phones and devices has proliferated almost all aspects of our lives. With that, each of us have become the producers and consumers of different types of data, of different levels of sensitivity, and of different levels of trustworthiness. One important aspect of managing such data on our devices and associated cloud (e.g., iCloud of Apple) is how to manage the authenticity such data. In this paper, we present a data model and a scheme towards assuring authenticity of the data. Our scheme is very efficient -- it computes only one signature.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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