1. Data and Applications Security Developments and Directions
Dr. Bhavani Thuraisingham
The University of Texas at Dallas
Lecture #17
Secure Data Warehousing
March 14, 2007

2. Outline Background on Data Warehousing What is a Data Warehouse?
Data Warehousing Technologies
Data Warehouse Design
Distributing the Data Warehouse
Data Modeling
Indexing
Security Issues for Data Warehousing

3. What is a Data Warehouse?
A Data Warehouse is a:
Subject-oriented
Integrated
Nonvolatile
Time variant
Collection of data in support of management’s decisions
From: Building the Data Warehouse by W. H. Inmon, John Wiley and Sons
Integration of heterogeneous data sources into a repository
Summary reports, aggregate functions, etc.

4. Example Data Warehouse
Users
Query
the Warehouse
Data Warehouse:
Data correlating
Employees With
Medical Benefits
and Projects
Could be
any DBMS;
Usually based on
the relational
data model
Oracle
DBMS for
Employees
Sybase
DBMS for
Projects
Informix
DBMS for
Medical

5. Some Data Warehousing Technologies
Heterogeneous Database Integration
Statistical Databases
Data Modeling
Metadata
Access Methods and Indexing
Language Interface
Database Administration
Parallel Database Management

6. Data Warehouse Design
Appropriate Data Model is key to designing the Warehouse
Higher Level Model in stages
Stage 1: Corporate data model
Stage 2: Enterprise data model
Stage 3: Warehouse data model
Middle-level data model
A model for possibly for each subject area in the higher level model
Physical data model
Include features such as keys in the middle-level model
Need to determine appropriate levels of granularity of data in order to build a good data warehouse

7. Distributing the Data Warehouse
Issues similar to distributed database systems
Branch A
Branch A
Branch B
Branch B
Branch B
Warehouse
Branch A
Warehouse
Central
Bank
Central
Bank
Central
Warehouse
Central
Warehouse
Non-distributed Warehouse
Distributed Warehouse

8. Multidimensional Data Model

9. Indexing for Data Warehousing
Bit-Maps
Multi-level indexing
Storing parts or all of the index files in main memory
Dynamic indexing

10. Metadata Mappings

11. Data Warehousing and Security
Security for integrating the heterogeneous data sources into the repository
e.g., Heterogeneity Database System Security, Statistical Database Security
Security for maintaining the warehouse
Query, Updates, Auditing, Administration, Metadata
Multilevel Security
Multilevel Data Models, Trusted Components

12. Example Secure Data Warehouse

13. Secure Data Warehouse Technologies

14. Security for Integrating Heterogeneous Data Sources
Integrating multiple security policies into a single policy for the warehouse
Apply techniques for federated database security?
Need to transform the access control rules
Security impact on schema integration and metadata
Maintaining transformations and mappings
Statistical database security
Inference and aggregation
e.g., Average salary in the warehouse could be unclassified while the individual salaries in the databases could be classified
Administration and auditing

15. Security Policy for the Warehouse
Federated Policy
Federated Policy
for Federation
for Federation F1 F2
Export Policy
Export Policy
Export Policy
Export Policy
for Component A
for Component B
for Component B
for Component C
Generic Policy
Generic Policy
Generic policy
for Component A
for Component B
for Component C
Component Policy
Component Policy
Component Policy
for Component A
for Component B
for Component C
Security Policy Integration and Transformation
Federated policies become warehouse policies?

16. Security Policy for the Warehouse - II

17. Secure Data Warehouse Model

18. Methodology for Developing a Secure Data Warehouse

19. Multi-Tier Architecture
Tier N: Secure Data Warehouse
Tier N: Data Warehouse
Builds on Tier N
Builds on Tier N - - 1 1 * *
Each layer builds on the Previous
Layer
Schemas/Metadata/Policies * *
Tier 2: Builds on Tier 1
Tier 2: Builds on Tier 1
Tier 1:Secure Data Sources
Tier 1:Secure Data Sources

20. Administration
Roles of Database Administrators, Warehouse Administrators, Database System Security officers, and Warehouse System Security Officers?
When databases are updated, can trigger mechanism be used to automatically update the warehouse?
i.e., Will the individual database administrators permit such mechanism?

21. Auditing Should the Warehouse be audited? Advantages
Keep up-to-date information on access to the warehouse
Disadvantages
May need to keep unnecessary data in the warehouse
May need a lower level granularity of data
May cause changes to the timing of data entry to the warehouse as well as backup and recovery restrictions
Need to determine the relationships between auditing the warehouse and auditing the databases

22. Multilevel Security Multilevel data models
Extensions to the data warehouse model to support classification levels
Trusted Components
How much of the warehouse should be trusted?
Should the transformations be trusted?
Covert channels, inference problem

23. Inference Controller

24. Status and Directions
Commercial data warehouse vendors are incorporating role- based security (e.g., Oracle)
Many topics need further investigation
Building a secure data warehouse
Policy integration
Secure data model
Inference control