Open Access
EPJ Web Conf.
Volume 251, 2021
25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
Article Number 02012
Number of page(s) 8
Section Distributed Computing, Data Management and Facilities
Published online 23 August 2021
  1. M. Mambelli, P. Mhashilkar, D. Box, I. Sfiligoi, D. Strain, et al., (2020) glideinWMS/glideinwms. Zenodo., accessed: 2021-06-06 [Google Scholar]
  2. M. Mambelli, T. Hein, GlideinMonitor. United States. accessed: 2021-06-06 [Google Scholar]
  3. J. Vasa, P Modi, Review of Different Privacy Preserving Techniques in PPDP , International Journal of Engineering Trends and Technology, IJETT, 59, 5 (2018),, accessed: 2021-06-06 [Google Scholar]
  4. K. Rajendran, M. Jayabalan, M.E. Rana, A Study on k-anonymity, l-diversity and t-closeness Techniques focusing Medical Data, International Journal of Computer Science and Network Security, IJCSNS, 17, 12 (2017) [Google Scholar]
  5. P. Samarati, L. Sweeney, Protecting privacy when disclosing information: K-anonymity and its enforcement through generalization and suppression. (2007) [Online] Available at:, accessed: 2021-06-06 [Google Scholar]
  6. L. Sweeney L. Achieving k-Anonymity Privacy Protection Using Generalization And Suppression, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, IJUFKS 10(5), pp. 571–588. (2002) doi: 10.1142/s021848850200165x. [Google Scholar]
  7. A. Machanavajjhala, D. Kifer, J. Gehrke and M. Venkitasubramaniam, L -diversity: privacy beyond k-anonymity, ACM Transactions on Knowledge Discovery from Data, 1(1). (2007) doi: 10.1145/1217299.1217302. [Google Scholar]
  8. N. Li, T. Li and S. Venkatasubramanian, Tcloseness: Privacy beyond k-anonymity and l-diversity, ICDE 2007 IEEE 23rd International Conference on Data Engineering, (2007) doi: 10.1109/icde.2007.367856. [Google Scholar]
  9. D. Bikel, R. Schwartz, R. Weischedel, An Algorithm that Learns What's in a Name, Machine Learning, 34 (1-3) pp. 211–231 (1999), accessed: 2021-06-06 [Google Scholar]
  10. F. Legger, V. Kuznetsov, C. Ariza Porras, C. Uzunoglu, R. Indra, The evolution of the CMS monitoring infrastructure, CHEP2021, to appear in the proceedings. [Google Scholar]

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