Privacy by Design : Big Privacy for Big Data

1. Privacy by Design: Big Privacy for Big Data 2013 Digital Odyssey: Big Data, Small World Ontario Library IT Association Toronto, Canada June 7, 2013

2. Overview • Introduction to IPC • Privacy 101 • Challenges to Privacy in the Age of Big Data • Privacy by Design • Big Privacy for Big Data

3. Ann Cavoukian, PhDOntario’s Information and Privacy Commissioner Ensure that government organizations (provincial and municipal) comply with freedom of information and privacy laws in Ontario Investigate privacy complaints and resolve appeals when the government refuses to grant access to government-held information Conduct research on and raise awareness of emerging privacy & access to information issues

4. IPC Philosophy: 3 C’s • Consultation: by keeping open lines of communication • Co-operation: rather than confrontation in resolving complaints • Collaboration: through working together to find solutions

5. Privacy 101 • Information privacy refers to the right or ability of individuals to exercise control over the collection, use and disclosure by others of their personal information • Personally-identifiable information (“PII”) can be biographical, biological, genealogical, historical, transactional, locational, relational, computational, vocational or reputational, and is the stuff that makes up our modern identity Personal information must be managed responsibly. When it is not, accountability is undermined and confidence in our evolving information society is eroded.

6. From PC to Web 4.0: Challenges to Privacy in the Age of Big Data Radar Networks & Nova Spivack, 2007

7. Wireless and Mobile: Beware of Unintended Consequences

8. Source: www.sciencedaily.com/releases/2013/03/130327132547.htm

9. “We need to be more deliberate (about privacy). A lot of information-age architecture is about data: what is collected, who controls it, and how it is used. Data is the lifeblood of the information age, but much of it is very personal. We need to design systems that limit unnecessary data collection, give individuals control over their data, and limit the ability of those in power to use that data for mass surveillance.” (Bruce Schneier, IEEE Security & Privacy January/February 2009 )

11. Data Assets = Data Risks and LiabilitiesThreats to Privacy

12. Data Privacy requires Good Data SecuritybutGood Data Security ≠ Privacy

13. Why We Need Privacy by Design Most privacy breaches remain undetected – as regulators, we only see the tip of the iceberg The majority of privacy breaches remain unchallenged, unregulated ... unknown Regulatory compliance alone, is unsustainable as the sole model for ensuring the future of privacy

14. Privacy by Design:The 7 Foundational Principles • Proactive not Reactive: Preventative, not Remedial • Privacy as the Default • Privacy Embeddedinto Design • Full Functionality: Positive-Sum, not Zero-Sum • End-to-End Security: Full Lifecycle Protection • Visibility and Transparency: Keep it Open • Respect for User Privacy: Keep it User-Centric

15. Privacy by Design FIPPs

16. Privacy by Design Information Technology www.privacybydesign.ca Physical Design & Infrastructure Accountable Business Practices

18. De-identification – Data Minimization Restoring the value of de-identification; Challenges in re-identifying de-identified information; The implications of including de-identified information under privacy legislation; Rejecting the zero-sum paradigm; Conducting re-identification risk assessment.

19. Data Co-management In the Web 2.0 era, information may very well “want to be free” but not necessarily personal information! • Data accountability • Data minimization • Data security • Data access The Big Idea: Data co-management – Citizen participation in the care and management of his/her own personal data held by others throughout the data life cycle

20. PERSONAL DATA ECOSYSTEM (PERSONAL DATA VAULT/PERSONAL DATA PLATFORM)

21. UI Design Concepts: Transparency & Trust • Context – think of the device as well as the context for how the information will be treated • Awareness – doesthe user know that privacy policies exist and that they can exercise choice • Discoverability – ease of finding relevant privacy policies & ease of acting on available privacy settings • Comprehension - consider if users can understand the privacy policies & privacy settings to be able to make an informed decision

22. Privacy by Design in the Age of Big Data and Sensemaking Systems • Ability of analytical tools to process & make sense of extremely large sets of structured and unstructured data • New class of analytic capability where the data finds the data and the relevance finds the user • Increase in accuracy of data – context reduces ambiguity • Accumulation of bad data = smarter system • As data store increases, context is enhanced = faster results • Requires Big Privacy!

23. PbD Features for Next-generation Sensemaking Systems • Full attribution: preserve record metadata; do not allow merge/purge processing • Data tethering: any changes to records must apply across the information sharing ecosystem in real-time • Analytics on anonymized data: anonymize data at source prior to transfer; utilize homomorphic encryption • Tamper-resistant audit logs: every user search logged, even database administrator • False negative favoring methods: trust but verify • Self-correcting false positives: reverse earlier assertions real-time and scaled • Information transfer accounting: capture data flows for discovery by individual

24. Patience, Persistence and Faith: The Chronicles of a Crusader “Your identity is your most valuable possession. Protect it. And if anything goes wrong, use your powers.” Helen (aka Elastigirl) The Incredibles Disney/Pixar 2004 Privacy by Design NOT Privacy by Disaster!

25. How to Contact Us Michelle Chibba, Director, Policy and Special Projects Information and Privacy Commissioner’s Office of Ontario 2 Bloor Street East, Suite 1400 Toronto, Ontario, Canada M4W 1A8 Phone: (416) 326-3333 / 1-800-387-0073 Web:www.ipc.on.ca E-mail:info@ipc.on.ca