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Article . 2019
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ACCOUNTABILITY AGAINST DISHONEST BIG DATA BUYERS AND SELLERS

Authors: M.S.Yasmine Fathima*1 & R.Sahila Devi2;

ACCOUNTABILITY AGAINST DISHONEST BIG DATA BUYERS AND SELLERS

Abstract

In this article, we proposed a set of accountable protocols denoted as AccounTrade for big data trading among dishonest consumers. For attaining secure big data trading environment. Throughout the trading (i.e., buying and selling of datasets) bookkeeping and accountability are achieved against consumers. Examines the consumer’s responsibilities in the data trading, and then designed AccountTrade to achieve accountability against dishonest consumers that are likely to deviate from their responsibility. Specially uniqueness index is defined and proposed it is a new measure of data uniqueness. Parallelization has been defined against overhead comes from the data file conversion to membership vector.

Keywords

AccontTrade, Uniqueness index, Accountability, Datatrading

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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).
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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.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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