By Josep Domingo-Ferrer
This publication constitutes the refereed complaints of the foreign convention on privateness in Statistical Databases, PSD 2014, held in Ibiza, Spain in September 2014 lower than the sponsorship of the UNESCO chair in info privateness. The 27 revised complete papers awarded have been conscientiously reviewed and chosen from forty-one submissions. The scope of the convention is on following issues: tabular info defense, microdata protecting, defense utilizing privateness types, man made information, list linkage, distant entry, privacy-preserving protocols, and case studies.
Read or Download Privacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference, PSD 2014, Ibiza, Spain, September 17-19, 2014. Proceedings PDF
Best data modeling & design books
This publication constitutes a suite of study achievements mature adequate to supply an organization and trustworthy foundation on modular ontologies. It supplies the reader an in depth research of the cutting-edge of the learn region and discusses the hot strategies, theories and methods for wisdom modularization.
Until eventually lately, details platforms were designed round diverse enterprise features, equivalent to debts payable and stock keep an eye on. Object-oriented modeling, by contrast, constructions structures round the data--the objects--that make up a number of the enterprise capabilities. simply because information regarding a specific functionality is restricted to at least one place--to the object--the procedure is protected against the results of swap.
Designed particularly for a unmarried semester, first path on database platforms, there are four features that differentiate our booklet from the remainder. simplicity - mostly, the expertise of database platforms could be very obscure. There are
Extra resources for Privacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference, PSD 2014, Ibiza, Spain, September 17-19, 2014. Proceedings
This is a way of creating uncertainty to a data user, and hence protecting the information provided by each respondent. In most of the cases this range of values is not explicitly given in the output, but it may be anyway computed by the user after the output has been published. That is the case when using cell suppression, for example. The user will solve two optimization problems to detect the extreme values defining the range of a cell in the output. These two mathematical problems for a given cell in the output are called “attacker problems” and the range of values is called “protected interval”.
CTA was original proposed by Dandekar and Cox (2002), and deeply analyzed later in Cox, Kelly, and Patil (2005). An excellent research with optimal and nearoptimal approaches to solve the MILP model is given in Glover, Cox, Kelly and Patil (2008). Castro and Giessing (2006) provide extensive experience applying CTA to real-world tables. Although CTA was originally proposed as a technique much simpler to implement than cell suppression, the optimization problem under CTA is also NP-hard and, in practice, the MILP model in CTA is far from trivial to be solved.
0046). For nonzero correlations there is no√evidence of change. Moreover, from Table 4 it is clear that relative changes in λ1 are a decreasing function of |ρ|. 4 (about 83%), and decreasing slowly beyond that point, both before and after the table protection. Figure 3 shows the ratio Z = π1,prot /π1,orig . 4% (Z ≈ 3 is out of the range of the vertical axis of Figure 3). Changes in π1 can be analyzed through Figure 3 and Table 5, which report the intervals with 90% of observed Z for diﬀerent ρ.