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2008
R. G. Pensa, Monreale, A., Pinelli, F., and Pedreschi, D., “Pattern-Preserving k-Anonymization of Sequences and its Application to Mobility Data Mining”, in PiLBA, 2008.
2010
A. Monreale, Trasarti, R., Renso, C., Pedreschi, D., and Bogorny, V., “Preserving privacy in semantic-rich trajectories of human mobility”, in SPRINGL, 2010, pp. 47-54.
2011
F. Giannotti, Lakshmanan, L. V. S., Monreale, A., Pedreschi, D., and Wang, H. Wendy, “Privacy-preserving data mining from outsourced databases.”, in the 3rd International Conference on Computers, Privacy, and Data Protection: An element of choice , 2011.
M. Berlingerio, Coscia, M., Giannotti, F., Monreale, A., and Pedreschi, D., “The pursuit of hubbiness: Analysis of hubs in large multidimensional networks”, J. Comput. Science, vol. 2, pp. 223-237, 2011.
2013
F. Pratesi, Monreale, A., Wang, H. Wendy, Rinzivillo, S., Pedreschi, D., Andrienko, G., and Andrienko, N., “Privacy-Aware Distributed Mobility Data Analytics”, in SEBD, Roccella Jonica, 2013.
A. Monreale, Wang, H. Wendy, Pratesi, F., Rinzivillo, S., Pedreschi, D., Andrienko, G., and Andrienko, N., “Privacy-Preserving Distributed Movement Data Aggregation”, in Geographic Information Science at the Heart of Europe, D. Vandenbroucke, Bucher, B., and Crompvoets, J., Eds. Springer International Publishing, 2013, pp. 225-245.
F. Giannotti, Lakshmanan, L. V. S., Monreale, A., Pedreschi, D., and Wang, H. Wendy, “Privacy-Preserving Mining of Association Rules From Outsourced Transaction Databases”, IEEE Systems Journal, 2013.
2014
A. Basu, Monreale, A., Corena, J. C., Giannotti, F., Pedreschi, D., Kiyomoto, S., Miyake, Y., Yanagihara, T., and Trasarti, R., “A Privacy Risk Model for Trajectory Data”, in Trust Management {VIII} - 8th {IFIP} {WG} 11.11 International Conference, {IFIPTM} 2014, Singapore, July 7-10, 2014. Proceedings, 2014, pp. 125–140.
A. Monreale, Rinzivillo, S., Pratesi, F., Giannotti, F., and Pedreschi, D., “Privacy-by-Design in Big Data Analytics and Social Mining”, EPJ Data Science, vol. 10, 2014.
2016
V. Grossi, Guns, T., Monreale, A., Nanni, M., and Nijssen, S., “Partition-Based Clustering Using Constraint Optimization”, in Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach, Springer International Publishing, 2016, pp. 282–299.
A. Monreale and Wang, H. Wendy, “Privacy-Preserving Outsourcing of Data Mining”, in 40th IEEE Annual Computer Software and Applications Conference, {COMPSAC} Workshops 2016, Atlanta, GA, USA, June 10-14, 2016, Atlanta, GA, USA, 2016.
A. Marrella, Monreale, A., Kloepper, B., and Krueger, M. W., “Privacy-Preserving Outsourcing of Pattern Mining of Event-Log Data-A Use-Case from Process Industry”, in Cloud Computing Technology and Science (CloudCom), 2016 IEEE International Conference on, 2016.
2017
F. Pratesi, Monreale, A., Giannotti, F., and Pedreschi, D., “Privacy Preserving Multidimensional Profiling”, in International Conference on Smart Objects and Technologies for Social Good, 2017.
2018
F. Pratesi, Monreale, A., Trasarti, R., Giannotti, F., Pedreschi, D., and Yanagihara, T., “PRUDEnce: a system for assessing privacy risk vs utility in data sharing ecosystems”, Transactions on Data Privacy, vol. 11, 2018.
2019
R. Pellungrini, Monreale, A., and Guidotti, R., “Privacy Risk for Individual Basket Patterns”, in ECML PKDD 2018 Workshops, Cham, 2019.
R. Pellungrini, Monreale, A., and Guidotti, R., “Privacy Risk for Individual Basket Patterns”, in ECML PKDD 2018 Workshops, Cham, 2019.
2020
F. Naretto, Pellungrini, R., Monreale, A., Nardini, F. Maria, and Musolesi, M., “Predicting and Explaining Privacy Risk Exposure in Mobility Data”, in Discovery Science, Cham, 2020.
F. Naretto, Pellungrini, R., Nardini, F. Maria, and Giannotti, F., “Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks”, in ECML PKDD 2020 Workshops, Cham, 2020.
F. Pratesi, Gabrielli, L., Cintia, P., Monreale, A., and Giannotti, F., “PRIMULE: Privacy risk mitigation for user profiles”, vol. 125, p. 101786, 2020.
2021
G. Mariani, Monreale, A., and Naretto, F., “Privacy Risk Assessment of Individual Psychometric Profiles”, in Discovery Science - 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021, Proceedings, 2021.