Tiancheng Li PhD Candidate Department of Computer Science Purdue University Mailing Address     Purdue University     Department of Computer Science     305 N. University Street     West Lafayette, IN 47907 Email li83 [at] cs.purdue.edu Phone 1-765-586-7289 CV [PDF][PS]

I am a PhD student in the Department of Computer Science at Purdue University.
My advisor is Prof. Ninghui Li, who is also the chair of my advisory committee.
Other members of my advisory committee are Prof. Elisa Bertino and Prof. Chris Clifton.
My research interests are in the area of data mining and database systems,
with an emphasis on data privacy and security.

Education

• Ph.D. in Computer Science, Purdue University, 2010 (expected).
• M.S. in Computer Science, Purdue University, 2008.
• B.S. in Computer Science, Zhejiang University, 2005.

Professional Services

• PC member, ACM International Workshop on Security and Privacy in GIS and LBS (SPRINGL 2009)
• Journal reviewer, TODS (2008), VLDB Journal (2009), TKDE (2008,2009), TKDD (2009)
• External reviewer, SIGMOD (2007, 2008), VLDB (2008, 2009), ICDE (2008)
• External reviewer, S&P (2007, 2008), CCS (2006, 2009), WWW (2009)

Research Projects [HTML, PDF]

Journal Articles

• [Paper in PDF] Closeness: A New Privacy Measure for Data Publishing
  Ninghui Li, Tiancheng Li, and Suresh Venkatasubramanian
  To appear in IEEE Transaction on Knowledge and Data Engineering (TKDE), 2009.
  

• [Paper in PDF] Privacy Preserving Incremental Data Dissemination
  Ji-Won Byun, Tiancheng Li, Elisa Bertino, Ninghui Li, and Yonglak Sohn
  In Journal of Computer Security (JCS), 17:(1) 43-68, 2009.
  

• [Paper in PDF] Towards Optimal k-Anonymization
  Tiancheng Li and Ninghui Li
  In Data & Knowledge Engineering Journal (DKE), 65:(1) 22-39, 2008.
  

Conference/Workshop Papers

• [Paper in PDF] On the (In)Security and (Im)Practicality of Outsourcing Precise Association Rule Mining
  Ian Molloy, Ninghui Li, and Tiancheng Li
  To appear in IEEE International Conference on Data Mining (ICDM), 2009.

• [Paper in PDF] Slicing: A New Approach to Privacy Preserving Data Publishing
  Tiancheng Li, Ninghui Li, Jian Zhang, and Ian Molloy
  In Preprints arXiv:0909.2290v1 [cs.DB], 2009.

• [Paper in PDF] WORM-SEAL: Trustworthy Data Retention and Verification for Regulatory Compliance
  Tiancheng Li, Xiaonan Ma, and Ninghui Li
  In European Symposium on Research in Computer Security (ESORICS), 2009.

• [Paper in PDF] On the Tradeoff Between Privacy and Utility in Data Publishing
  Tiancheng Li and Ninghui Li
  To appear in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2009.

• [Paper in PDF] Evaluating Role Mining Algorithms
  Ian Molloy, Ninghui Li, Tiancheng Li, Ziqing Mao, Qihua Wang, and Jorge Lobo
  In ACM Symposium on Access Control Models and Technologies (SACMAT), pp. 95-104, 2009.
  

• [Paper in PDF] Modeling and Integrating Background Knowledge in Data Anonymization
  Tiancheng Li, Ninghui Li, and Jian Zhang
  In IEEE International Conference on Data Engineering (ICDE), pp. 6-17, 2009.

• [Paper in PDF] Block Size Optimization in Deduplication Systems
  Cornel Constantinescu, Jan Pieper, and Tiancheng Li
  In Data Compression Conference (DCC), pp. 442, 2009.

• [Paper in PDF] Mining Roles with Semantic Meanings
  Ian Molloy, Hong Chen, Tiancheng Li, Qihua Wang, Ninghui Li, Elisa Bertino, Seraphin Carlo, and Jorge Lobo
  In ACM Symposium on Access Control Models and Technologies (SACMAT), pp. 21-30, 2008.
  

• [Paper in PDF] Injector: Mining Background Knowledge for Data Anonymization
  Tiancheng Li and Ninghui Li
  In IEEE International Conference on Data Engineering (ICDE), pp. 446-455, 2008.

• [Paper in PDF] t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
  Ninghui Li, Tiancheng Li, and Suresh Venkatasubramanian
  In IEEE International Conference on Data Engineering (ICDE), pp. 106-115, 2007.
  

• [Paper in PDF] Optimal k-Anonymity with Flexible Generalization Schemes through Bottom-Up Searching
  Tiancheng Li and Ninghui Li
  In IEEE International Workshop on Privacy Aspect of Data Mining (PADM), in conjunction with ICDM, pp. 518-523, 2006.

Last modified on June 17, 2009