Recommended
Recommended
More Related Content
Viewers also liked
Similar to Overview of Policies for Security and Data Sharing in PALMS System
Similar to Overview of Policies for Security and Data Sharing in PALMS System (20)
More from bdemchak
More from bdemchak (20)
Recently uploaded
Recently uploaded (20)
Overview of Policies for Security and Data Sharing in PALMS System
- 1. Overview of Policies for Security and Data Sharing Ingolf Krüger Barry Demchak March 16, 2010
- 2. Roadmap • PALMS (Physical Activity Location Measurement System) • SOA Review • PALMS Logical Architecture • Policy and its composition • Policy execution – relationship with caBIG Feel free to ask questions!
- 3. PALMS Objectives • Support data collection and analysis for exposure biology studies – Data capture from multiple devices – Multiple analyses and recombination of data – Sharing of data between investigators and projects – Support multiple visualizations (local and remote) • Extensible and Flexible – Scalable for large data flows – Support large number of investigators and studies – Customizable datasets, calculations, and visualizations • HIPAA Compliant and Secure
- 4. PALMS Organization and Data Flow (CI) Authorable & Discoverable
- 5. Study Repository Study Repository Visualizatio n Repository Visualizatio n Repository Calculation Repository Calculation Repository PALMS Community PI Study Study Study PI Study Study PI Study PALMSPALMS StudyStudyStudy Study StudyStudy PI PI PI Community • Policy-driven access control – Subject data – Study data – Calculations – Visualizations • Secure • HIPAA Compliance • Customized Studies • Collaboration • Data Reuse Browser Excel, Matlab…
- 6. Study Repository Study Repository Visualizatio n Engine Visualizatio n Engine Calculation Engine Calculation Engine Data Flow PALMSPALMS StudyStudyStudy Study StudyStudy PI RA Define Enter Subjects Enter Observations Refine & Start Refine & Create Guest
- 7. Study Repository Study Repository Visualizatio n Engine Visualizatio n Engine Calculation Engine Calculation Engine Policy PALMSPALMS StudyStudyStudy Study StudyStudy PI RA Guest Policy Policy Admin Defines Policy (def.): Permission for someone to act on something Uses Applies Policy (alt def.): Conditional replacement of one workflow with another
- 8. Services and SOA • Loose Coupling • Late Binding • Scalability • Composition • Interoperability • Testability Network Implementation Single Server, Multiple Processes Single Application, Linked Modules Logical Deployment • Malleability • Manageability • Dependability • Incremental development
- 10. Composing Workflow and Policy • Define and implement Policy Concerns – A class of policy decision embedded in a workflow – Characterized by a contract for workflow and dataflow – Supports reasoning regarding application correctness, completeness, and contradiction – Instantiated as policies inserted by stakeholders at either design time or runtime If user in [“PIs”, “RAs”, “Guests”] Continue Else Reply “Failure”
- 11. Groups and Roles If user in [“PIs”, “RAs”, “Guests”] Continue Else Reply “Failure” • Internet2 Grouper – Hierarchical group management – Single point of control – Permission-based administration – Virtual organizations (VOs)
- 12. Identity If user in [“PIs”, “RAs”, “Guests”] Continue Else Reply “Failure” • Establishing – What I have (token) – What I know (password) – What I am (biometric) • Referencing – Trust relationships (certification authorities) – X509 Certificate – SAML Certificate – OpenID Browser Application 3 2 1 Certificate 4 5 User ID & Password Confirm ID Provider
- 13. caBIG cancer Biomedical Informatics Grid – Connects scientists & practitioners: shareable & interoperable infrastructure – Develop standard rules & common language: easily share information – Tools: collecting, analyzing, integrating, disseminating cancer information – Cornerstones – Federation – Open development – Open access – Open source – Workspaces – Clinical Trial Management – Integrative Cancer Research – Tissue Banks and Pathology – Vocabularies & Common Data Elements – Architecture – Strategic Planning – Data Sharing and Intellectual Capital – Training
- 14. caGrid & GAARDS • Grid Authentication & Authorization with Reliably Distributed Services – Services & Tools for enforcement of security policy in enterprise grid – Developed on Globus Toolkit – Provides – grid user management – identity federation – trust fabric provisioning and management – group/VO management – access control policy management and enforcement – credential delegation – web SSO – integration between security domains & grid security domain
- 15. caGrid & GAARDS
- 16. Relationship to PALMS • Pros – Well supported – caGrid Knowledge Center (Justin Permer/Ohio State Bioinformatics) – Professionally managed – Well developed governance and development models – Standards-based – Security: X509 & SAML – Ontologies: Thesaurus and Metathesaurus – Sharing infrastructure – Growing community • Cons – Key infrastructure out of our direct control
- 17. Questions??
- 18. Backup slides
- 19. Composing Workflow and Policy Scenario: Add Policy to Existing Workflow (CNN | BBC) > story > if(authorized) > email(story,”x@ucsd.edu”) • Key issues – What is policy to compose? – Where to insert policy? ... capture all paths? – How to compose multiple policies? – How to guarantee integrity of workflow? – Preview: We have to address these • Current methodologies – Requirement discovery and hand coding – Policy-based design & Inversion of Control – Aspect Oriented Programming – UML sequence chart composition • New methodology (preview) – ORCA
- 20. Architecture Definition Methodology Rich Services VirtualNetwork Rich Services RAS4 Services Service S 1 Roles U1 U2 U3 U4 U5 Use Case Graph Concerns C1 C2 C3 C4 CC1 CC2CC3 Domain Model R1 R2 R3 R4 R5 R6 R1 R2 msg R3 CC1 CC2 Role Domain Model R1 R2 R3 R4 R5 R6 CC1 CC2 CC3 Router/Interceptor Messenger /Communicator RAS1 RAS2 CC1 CC4 CC5 Router /Interceptor Messenger / Communicator RAS5 RAS6RAS3 S / D S / D RIS: RIS: ServiceElicitationRichServiceArchitecture RAS7 Systemof Systems Topology H1 H2 H3 H5 H6 H7 H8 H9 H4 RAS1 RAS2 RAS3 RAS5 RAS6 RAS7 Infrastructure Mapping H1:RAS1 H2:RAS2 H3:CC1 H5:RAS2 H6:RAS5 H7:RAS7H8:RAS7 H9:RAS6 H4:RAS3Optimization Implementation RAS1 RAS 2 RAS3 RAS 4 RAS5 RAS 6 RAS7 CC1 CC2 CC3 CC4 CC5 Analysis Synthesis Analysis Identification Definition Consolidation Refinement Hierarchic composition Refinement Logical Model SystemArchitecture Definition Logical Architecture Loop DeploymentLoop
- 21. User View
- 25. Artifacts • User Stories • Use Cases • Access Control Patterns • Domain Modeling • Dataflow • Low Fidelity UI • Service Definitions • Rich Service Requirements Modeling Service Modeling
- 26. Use Cases
- 27. Use Case Attributes • ID • Name • Priority • Complexity • Release Number • Last Revised • Description • Actors (Primary and Secondary) • Stakeholders • Pre-Conditions • Constraints • Post-Conditions • Triggers • Cross References • Flow of Events – Basic Flow – Alternative Flows – Exceptions • Extensions • Information Requirements • Special Requirements • Frequency of Use • Assumptions • Issues and Considerations – Issues – Consideration • Process Flows • Related Use Cases RA signs in RA selects study RA uploads .CSV and .GPX files PALMS displays summary RA confirms summary PALMS commits dataset PALMS abandons dataset Display error Display error All files missing or invalid Time range overlaps accept decline
- 28. Low Fidelity User Interface
- 30. Domain Modeling
- 31. Rich Service
- 33. Service Interactions (Calculation) alt alt Web Browser PALMS Study Calculation Engine StartCalculation(study, protocolID, paramBlockID, resultName) StartResult - study + study Start Calculation Results Repository Initiate Result AddResult(resultName, protocolID, paramBlock) AddResult Protocol Repository GetProtocolParams(protocolID, paramBlockID) Get Param Block ParamBlockResult
- 34. The Road ForwardComponent Interactions Client Server Server Google Web Toolkit (GWT) Mule Enterprise Service Bus
- 35. PALMS Products • Integration – Mapping Engines – Data Mining Engines – Social Networks – Disaster Management • Alerts and Events • Data Subscriptions • Data Flow Analysis (provenance flow) • Scalable and Configurable Calculations • Collaboration
- 36. Questions??
Editor's Notes
- <number> Thank the host!
- In the beginning: PIs have their studies, and their studies have their data, calculations, and visualizations ----- Insight: Studies can be managed centrally; calculations and visualizations can be reused; collaborations can occur with data, calculations, and visualizations Click 1: Enter PALMS, an Internet-based facility for managing research Click 2: The main features of PALMS: the study repository, calculation repository, and visualization repository Click 3: Community uses PALMS to manage studies, provide calculations, and provide visualizations Click 4: Policy -> HIPAA, Collaboration, etc
- PALMS is a role-based system. Data flows are associated with particular roles and particular targets Click 1: A PI can define what data a study retains, what calculations can be made, and what visualizations can be made Click 2: An RA can enter subject and observation information Click 3: Once the information exists in the study, the RA can send it to a calculation engine, and then to a visualizer Click 4: A guest cannot enter data, but can get calculations and visualizations All data flows and requests are subject to policy (next slide)
- Policy can be defined at both the PALMS system level and at the study level Click 1: What is a policy? Click 2: Who defines policies?? … it depends on the policy … (RAs can define policies that affect guests) Click 3: An example: A guest wants to run a calculation and get a visualization Click 4: Policy at both the PALMS and study level apply to allow/reject the operation, or to constrain or shape it Important points: - Policy can be used for access control and HIPAA enforcement. - Policy engines monitor all transactions. - Policy engines not only enforce permissions, but they also cause audit logging - Engines similar to the policy engines can also perform encryption, anonymization, decimation, failure management, and so on
- Current methodologies Requirement discovery and hand coding Policy-based design & Inversion of Control Aspect Oriented Programming UML sequence chart composition New methodology (preview) ORCA
- Add Authentication policy into CNN/BBC workflow … see red decision-making <<<<CLICK>>>> In ORC, see the same decision being inserted <<<<CLICK>>>> <<Go over key issues>> To solve the policy insertion problem, we have to solve these <<<<CLICK>>>> Show existing well-known solutions … not reactive to stakeholder policy insertion <<<<CLICK>>>> ORCA is part of solution … specifies WHAT and WHERE