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Healthcare Group: The 12 Stories

Healthcare Group: The 12 Stories. Peng (group lead), Paul, Bhavani, Le, Gail, Prabhakaran, Khan, Murat Feb 19-20, 2009 NSF Data & Application Security Workshop Arlington, VA. The Context (1). electronic records & handwritten physician notes coexist. electronic records everywhere.

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Healthcare Group: The 12 Stories

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  1. Healthcare Group: The 12 Stories Peng (group lead), Paul, Bhavani, Le, Gail, Prabhakaran, Khan, Murat Feb 19-20, 2009 NSF Data & Application Security Workshop Arlington, VA

  2. The Context (1) electronic records & handwritten physician notes coexist electronic records everywhere Obama's healthcare policy: -Improved health; -Reduced costs EHR national standard Current status Future

  3. The Context (2) • Data characteristics • Structured; • unstructured; • semi-structured; • multimedia • time-series; data stream; • temporal vs. spatial dimensions • 1: Patient records at hospital and across hospitals • 2: Remote healthcare at home • 3: Data sharing for research • 4: Doctors consult with other doctors • 5: Medical info system • Billing fraud • 6: Cyber-physical systems • Bugs in heart monitors

  4. The main security issues

  5. Integrity + Current (1) • Story 1: The Oklahoma state children health care database is a set of records contributed by physicians at multiple hospitals • The database is used to generate official state level statistics • The database cannot generate correct statistics • Reason: the same kid has multiple records: “baby A” “baby B” “last name 1” “last name 2” • Research problem: the attribution problem

  6. Integrity + Current (2) • Story 2: My doctors or nurses or lab technicians make mistakes; they told me that I am now 50 pounds heavier. • Reality checks • Consistency checks • Some kind of alarming measures • Bigger research question: How to systematically cleanse health records?

  7. Integrity + Transition • Story 3: To create jobs, people are hired to type physicians’ handwritten notes into computers • How to alert human typing errors in real time? • Are these people trusted? • Do they really understand the notes?

  8. Privacy + Current (1) • Story 4: A patient’s doctor wants to consult with other doctors (via an online forum) to get comments and second opinions: • How much to disclose? • How much is too much? • Via the online forum, indirect inference attack could succeed through attribute aggregation & correlation (between related postings) • Can the patient have any “control” of this process? • Economic and social issues

  9. Privacy + Current (2) Story 5: For research purpose, a provider can multicast need-driven data requests to her federated partners. Result: Patient records pulled together then used by researchers: great privacy threat • How to accommodate patients’ concerns during data gathering? • Privacy aware patient record integration • Patient record set anonymization • Group based inference • Purpose driven access control (PDAC) • The government may have a different purpose from researchers • How to do selective sharing? • Policy requirements

  10. Privacy + Current (3) • Story 6: RHIO (Regional Health Inter-Organization) systems are being promoted by federal and state governments to let providers share patient records: • Privacy threats: • Query content privacy • Data location privacy • Patient location privacy • How to construct privacy preserving RHIO systems?

  11. Fraud + Current • Story 7: Doctor double charging multiple insurance companies; insurance company double billing • Fraud detection • Collusion attack • Healthcare info system auditing

  12. Integrity + Current (3) • Story 8: Bugs in medical devices could kill people (see Kevin Fu’s paper). • In remote healthcare, could a criminal misuse the remote control channel to trigger bugs? • Bug isolation

  13. Integrity + Current (4) • Story 9: Data tampering leads to wrong diagnosis. • Prevent tampering: tampering proof • Integrity check • Tampering of real time health condition monitoring data

  14. Privacy + Current (4) • Story 10: My hospital shares my X-Ray images with researchers; however, these images could be used to reconstruct (the shape of) my face  hurt privacy • Privacy preserving digital image processing

  15. Privacy + Current (5) • Story 11: In remote healthcare, monitors send a data stream of health data to a remote doctor: • Correlation attacks to infer sensitive medical condition • Time is critical: time series analysis

  16. Privacy + Current (6) • Story 12: A patient sits with doctor Bob at hospital A, asking for information from hospital B • The answer from hospital B: I need to ask my lawyer  now this process discontinues • Could need new delegation models • Need some assurance mechanisms

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