The main research track of KDDLab in the field of Complex Networks is Multidimensional Network Analysis. Traditionally, Complex Network Analysis has been monodimensional: researchers focused their attention to network with a single kind of relation represented. KDDLab is pushing the research over multidimensional networks, i.e. network with multiple kind of relations, since they are a better model to represent the complexity in reality (transportation, infrastructure and social networks are often multidimensional). In this novel scenario, we want to develop a basic theory and simple analytical measures, as well as more complex analysis and algorithms, such as community discovery, link prediction and the analysis of highly connected nodes (i.e. hubs). From the main multidimensional network research, different branches have emerged: we are investigating also mobility networks, using human trajectories as edges to connect different geographical areas and/or points of interest. Also, we have interest in analyze trust networks, particularly the problem of identifying possible privacy and/or security fallacies: is it possible that following a path of "trusted" individuals the information can be lead to an individual not trusted by the source of the information?