ACCOUNT TRADE: ACHIEVING DATA TRUTHFULNESS AND PRIVACY PRESERVATION IN DATA MARKETS

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. Bookkeeping and accountability are achieved against consumers throughout trading. 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. To avoid result from being manipulated by a false-name binding attack, we propose a Multi-round False-name Proof Auction (MFPA) scheme, which enables data trading among data owners (sellers) and data collectors (buyers).