Supporting techniques for knowledge discovery

Reporting on Task 4.1 findings, including: • Selection of a set of training/testing data sets for each problem to be solved. • Definition and first implementation of algorithms for predictive analysis, taking into account the low frequency of the events of interest • Performance evaluation of the algorithms, in terms of accuracy and speed, for the training/testing datasets • Definition and implementation of algorithms for causality analysis between sets of multivariate data, both static and time evolving (i.e. time series) and definition and implementation of advanced ways of representing causality relationships, e.g. by means of complex networks of relations. • Development of ways for including causality analysis in standard data mining algorithms. • Identification of suitable SMC primitives and protocols for performing secure computations. • Assessment of the computational cost of each devised solution (both for predictive analytics, causality and secure computation), and development of parallelisation strategies. • Definition of security test plans.