0000000001330094
AUTHOR
Francesco Randazzo
Experimental evaluation of privacy-preserving aggregation schemes on planetlab
New pervasive technologies often reveal many sen- sitive information about users’ habits, seriously compromising the privacy and sometimes even the personal security of people. To cope with this problem, researchers have developed the idea of privacy-preserving data mining which refers to the possibility of releasing aggregate information about the data provided by multiple users, without any information leakage about individual data. These techniques have different privacy levels and communication costs, but all of them can suffer when some users’ data becomes inaccessible during the operation of the privacy preserving protocols. It is thus interesting to validate the applicability of such…
e-Fair: Aggregation in e-Commerce for Exploiting Economies of Scale
In recent years, many new and interesting models of successful online business have been developed, including competitive models such as auctions, where the product price tends to rise, and group-buying, where users cooperate obtaining a dynamic price that tends to go down. We propose the e-fair as a business model for social commerce, where both sellers and buyers are grouped to maximize benefits. e-Fairs extend the group-buying model aggregating demand and supply for price optimization as well as consolidating shipments and optimize withdrawals for guaranteeing additional savings. e-Fairs work upon multiple dimensions: time to aggregate buyers, their geographical distribution, price/quant…