Invited Paper.- An Ad Omnia Approach to Defining and Achieving Private Data Analysis.- Contributed Papers.- Phoenix: Privacy Preserving Biclustering on Horizontally Partitioned Data.- Allowing Privacy Protection Algorithms to Jump Out of Local Optimums: An Ordered Greed Framework.- Probabilistic Anonymity.- Website Privacy Preservation for Query Log Publishing.- Privacy-Preserving Data Mining through Knowledge Model Sharing.- Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers.- Towards Privacy-Preserving Model Selection.- Preserving the Privacy of Sensitive Relationships in Graph Data.
