Systematic Control and Management of Data Integrity, Quality and Provenance for Command and Control Applications
Abstract
The objective of this project is to design and develop a comprehensive approach to the problem of assuring high data integrity able to support data analysis and decision making. The project has achieved the several novel results: (l) Digital signatures techniques for graph and tree structured data; the techniques are both hiding and binding, that is, they assure integrity without releasing information (unlike the Merkle hash tree technique that leaks information). (2) Efficient privacy-preserving data matching protocols; these protocols use a combination of data sanitization techniques, like differential privacy, with secure multi-party computation techniques. (3) A model to assess the trustworthiness of data based also on provenance information; the model has been applied to sensor data and location data. (4) An assessment of the use of sanitized data for classification tasks: through extensive experiments, we have shown that classifiers obtained from sanitized data are usually good. (5) A system to enforce application-defined integrity policies and its implementation on top of the ORACLE DBMS.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 24, 2010
- Accession Number
- ADA518609
Entities
People
- Elisa Bertino
Organizations
- Purdue University