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

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

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.

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

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

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

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

Multidimensional Data Model

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

Metadata Mappings

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

Example Secure Data Warehouse

Secure Data Warehouse Technologies

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

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?

Security Policy for the Warehouse - II

Secure Data Warehouse Model

Methodology for Developing a Secure Data Warehouse

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

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?

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

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

Inference Controller

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