SEDS 541
Privacy Preserving Data Sharing and Management
The specific topics include advanced concurrency control techniques, query processing and optimization strategies for relational database systems, advanced indexing methods, parallel and distributed database systems, next-generation data models, data mining on large databases, data on the web, and topics in data security and privacy.
Course Objectives
1.Learn advanced topics of database field (1)
2.Gain ability to capture research articles (2, 3, 4),
3.Gain ability to make a survey, propose solution and develop a project (4, 5).
Recommended or Required Reading
E.F. CODD. A Relational Model of Data for Large Shared Data Banks, Coomunication of the ACM, vol 15, June 1970 ,P.G. SELLINGER, M.M. ASTRAHAN, D.D. CHAMBERLIN, R.A. LORIE and T.G. PRICE, Access Path Selection in a Reletional Database System, ACM, 1979 ,S.CHAUDHURI, An Overview of Query Optimization in Relational Systems, PODS 1998 ,A. GUTTMAN. R-TREES. A Dynamic Index Structure for Spatial Searching, ACM 1984 ,J. NIEVERGELT and H. HINTERBERGER. The Grid File: An Adaptable, Symmetric Multikey File Structure, ACM 1984 ,D.J. DeWITT and J. GRAY.Parallel Database Systems: The Future of High Performance Database Processing, Communications of the ACM, Vol. 36, No. 6, June 1992 ,P.O’NEAL and D. QUASS. Improved Query Performance with Variant Indexes, ACM 1997 ,M. STONEBRAKER, P. M. AOKI, W. LITWIN, A. PFEFFER, A. SAH, J. SIDELL, C. STAELIN, A. YU. Mariposa: a wide-area distributed database system, The VLDBJournal, Springer-Verlag 1996 ,R. SNODGRASSF and I. AHN. A Taxonomy of Time in Databases, ACM, 1985 ,R. AGRAWAL and R. SRIKANT. Fast Algorithms for Mining Association Rules, Proceedings of the 20th VLDB ConferenceSantiago, Chile, 1994 ,J. GRAY, S. CHAUDHURI, A. BOSWORTH, A. LAYMAN, D. REICHART and M. VENKATRAO. Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals, Data Mining and Knowledge Discovery 1, 29–53 (1997) ,S. BRIN and L. PAGE The Anatomy of a Large-Scale Hypertextual Web Search Engine, Proceeding of 7th International Conference on World Wide Web, 1998 ,C.J. Date, An Introduction to Database Systems, Addison-Wesley, Seventh Edition, 2010
Learning Outcomes
1.Learn the history and development of aproaches and methods behind the functions of database management system (PO1, PO3),
2.Gain ability to read, abstract and discuss the important articles of the feld (PO1, PO3),
3.Analyze one of the open problems of database field (PO2),
4.Propose a solution to the open problem analyzed (PO2),
5.Present the project covering his reserach and proposal orally and written (PO6)
| Week | Topics |
|---|---|
| 1 | Introduction to Privacy Preserving Data Mining and Association Rule Hiding |
| 2 | Background (Terminology and Preliminaries) |
| 3 | Classes of Association Rule Hiding Methodologies |
| 4 | Other Knowledge Hiding Methodologies |
| 5 | Heuristic Approaches |
| 6 | Border Based Approaches |
| 7 | Max–Min Algorithms (BBA Algorithm) |
| 8 | Max–Min Algorithms (Other) |
| 9 | Exact Hiding Approaches (Menon’s Algorithm) |
| 10 | Exact Hiding Approaches (Inline Algorithm) |
| 11 | Exact Hiding Approaches (Two–Phase Iterative Algorithm) |
| 12 | Exact Hiding Approaches (Hybrid Algorithm) |
| 13 | Exact Hiding Approaches (Parallelization Framework) |
| 14 | Quantifying the Privacy of Exact Hiding Algorithms |
Grading
Midterm 30%
Research Presentation 30%
Final 40%