In this deliverable, we report of the following results:

- Implementation and evaluation of differential privacy methods on top of the Sharemind SMC framework. These methods allow us to check that the results of statistical analysis do not contain sensitive information traceable back to particular individuals.
- An algorithm to find the minimum spanning tree of a graph in a privacy-preserving manner
- A string matching algorithm, to find whether a given pattern string is contained in a larger text in a privacy-preserving manner.
- An algorithm to compute shortest distances in sparse graphs, where the lengths of the edges, as well as the structure of the graph itself, are private.
- A privacy preserving algorithm for Frequent Itemset Mining (FIM), which , given a collection of sets, finds the subsets of elements that are present in sufficiently many of these sets.
- Privacy preserving algorithms for Business Process Engineering, which focus on inferring (and checking correctness of ) the possible behavior of collaborating (but competitive) enterprises.