UTD CS 6V81 - LECTURE NOTES - D1011078

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UTD CS 6V81 - LECTURE NOTES

School name The University of Texas at Dallas

Course Cs 6v81- Independent Study In Computer Science Real Time Data Process In Andr

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Data and Applications Security Developments and DirectionsOutlineWhat is a Data Warehouse?Example Data WarehouseSome Data Warehousing TechnologiesData Warehouse DesignDistributing the Data WarehouseMultidimensional Data ModelIndexing for Data WarehousingMetadata MappingsData Warehousing and SecurityExample Secure Data WarehouseSecure Data Warehouse TechnologiesSecurity for Integrating Heterogeneous Data SourcesSecurity Policy for the WarehouseSecurity Policy for the Warehouse - IISecure Data Warehouse ModelMethodology for Developing a Secure Data WarehouseMulti-Tier ArchitectureAdministrationAuditingMultilevel SecurityInference ControllerStatus and DirectionsData Mining for Counter-terrorismData Mining Needs for Counterterrorism: Non-real-time Data MiningData Mining for Non Real-time ThreatsData Mining Needs for Counterterrorism: Real-time Data MiningData Mining for Real-time ThreatsData Mining Outcomes and Techniques for Counter-terrorismExample Success Story - COPLINKWhere are we now?What are our challenges?IN SUMMARY:Data and Applications Security Developments and DirectionsDr. Bhavani ThuraisinghamThe University of Texas at DallasData Warehousing, Data Mining and SecurityNovember 14, 2011OutlineBackground on Data WarehousingSecurity Issues for Data WarehousingData Mining and SecurityWhat 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 WarehouseOracleDBMS forEmployeesSybaseDBMS forProjectsInformixDBMS forMedicalData Warehouse:Data correlatingEmployees WithMedical Benefitsand ProjectsCould beany DBMS; Usually based on the relational data modelUsersQuerythe WarehouseSome Data Warehousing TechnologiesHeterogeneous Database IntegrationStatistical DatabasesData ModelingMetadataAccess Methods and IndexingLanguage InterfaceDatabase AdministrationParallel Database ManagementData 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 warehouseDistributing the Data WarehouseIssues similar to distributed database systemsDistributed WarehouseCentral BankBranch A Branch BCentralWarehouseCentralBankBranch ABranch BCentralWarehouseBranch BWarehouseBranch AWarehouseNon-distributed WarehouseMultidimensional Data ModelProject NameProject LeaderProject SponsorProject CostProject DurationDollarsPoundsYenYearsMonthsWeeksProject NameProject LeaderProject SponsorProject CostProject DurationDollarsPoundsYenYearsMonthsWeeksIndexing for Data WarehousingBit-MapsMulti-level indexingStoring parts or all of the index files in main memoryDynamic indexingMetadata MappingsMetadatafor Data source AMetadatafor Data source BMetadatafor Data source CMetadata for Mappings and TransformationsMetadata for Mappings and TransformationsMetadata for Mappings and TransformationsMetadatafor the WarehouseMetadatafor Data source AMetadatafor Data source BMetadatafor Data source CMetadata for Mappings and TransformationsMetadata for Mappings and TransformationsMetadata for Mappings and TransformationsMetadatafor the WarehouseData 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 ComponentsExample Secure Data Warehouse Secure Data Warehouse ManagerSecure DBMS A Secure DBMS BSecure DBMS CSecureDatabaseSecureDatabaseSecureDatabaseUserSecure WarehouseSecure Data Warehouse Technologies Secure Data Warehousing Technologies:Secure data modelingSecure heterogeneous database integrationDatabase securitySecure access methods and indexingSecure query languagesSecure database administrationSecure high performance computing technologiesSecure metadata managementSecurity 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 auditingSecurity Policy for the WarehouseFederated policies become warehouse policies?Component Policy for Component AComponent Policy for Component BComponent Policy for Component CGeneric Policy for Component AGeneric Policy for Component BGeneric policy for Component CExport Policy for Component AExport Policy for Component BExport Policy for Component CFederated Policy for Federation F1Federated Policy for Federation F2Export Policy for Component BSecurity Policy Integration and TransformationSecurity Policy for the Warehouse - II Policyfor the WarehousePolicyFor Data Source APolicyFor Data Source BPolicyFor Data Source CPolicy forMappings andTransformationsPolicy forMappings andTransformationsPolicy forMappings andTransformationsSecure Data Warehouse ModelDollars, SPounds, SYen, SYear, UMonths, UWeeks, UProject Name, U Project Leader, UProject Sponsor, SProject Cost, SProject Duration, UU = UnclassifiedS = SecretMethodology for Developing a Secure Data WarehouseIntegrateSecuredatasourcesClean/modifydataSources.IntegratepoliciesSecure datasourcesBuild securedata model,schemas,accessmethods,and indexstrategies forthe securewarehouseMulti-Tier ArchitectureTier 1:Secure Data SourcesTier 2: Builds on Tier 1Tier N: Data WarehouseBuilds on Tier N-1**Tier 1:Secure Data SourcesTier 2: Builds on Tier 1Tier N: Secure Data WarehouseBuilds on Tier N-1**Each layer builds on the Previous LayerSchemas/Metadata/PoliciesAdministrationRoles of

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