Welcome to Privacy and Big Data Analytics by Design

Ann Cavoukian, Ph.D.

Executive Director

Privacy and Big Data Institute Ryerson University

Welcome to Privacy and

Big Data Analytics – by Design

Privacy by Design Seminar

Presentation Outline

1. Privacy = Personal Control

2. Privacy is Essential to Freedom

3. Lead with Privacy by Design

4. Big Data Analytics

5. Privacy is Good for Business

6. SmartData

Privacy

≠

Secrecy

Privacy is not about having

something to hide

Privacy = Personal Control

• User control is critical

• Freedom of choice

• Informational self-determination

Context is key!

Privacy is Essential to Freedom:

A Necessary Condition for Societal Prosperity

and Well-Being

• Innovation, creativity, and the resultant prosperity of a society requires freedom;

• Privacy is the essence of freedom: Without privacy,

individual human rights, property rights and civil liberties – the conceptual engines of innovation and creativity, could not exist in a meaningful manner;

• Surveillance is the antithesis of privacy: A negative consequence of surveillance is the usurpation of a person’s

Change the Paradigm to

Positive-Sum,

NOT

Zero-Sum

The Future of Privacy:

Be Proactive

Landmark Resolution Passed to Preserve the Future of Privacy

By Anna Ohlden – October 29th 2010 -http://www.science20.com/newswire/landmark_resolution_passed_preserve_future_privacy

JERUSALEM, October 29, 2010 – A landmark Resolution by Ontario's Information

and Privacy Commissioner, Dr. Ann Cavoukian, was approved by international Data Protection and Privacy Commissioners in Jerusalem today at their annual conference. The resolution recognizes Commissioner Cavoukian's concept of Privacy by Design -which ensures that privacy is embedded into new technologies and business practices, right from the outset - as an essential component of fundamental privacy protection.

Full Article:

http://www.science20.com/newswire/landmark_resolution_passed_preserve_future_privacy

Adoption of “Privacy by Design”

as an International Standard

1. English 2. French 3. German 4. Spanish 5. Italian 6. Czech 7. Dutch 8. Estonian 9. Hebrew 10.Hindi 11.Chinese 12.Japanese 13. Arabic 14. Armenian 15. Ukrainian 16. Korean 17. Russian 18. Romanian 19. Portuguese 20. Maltese 21. Greek 22. Macedonian 23. Bulgarian 24. Croatian 25. Polish 26. Turkish 27. Malaysian 28. Indonesian 29. Danish 30. Hungarian 31. Norwegian 32. Serbian 33. Lithuanian 34. Farsi 35. Finnish 36. Albanian 37. Catalan

Privacy by Design:

Proactive in 37 Languages!

Privacy by Design’s Greatest Strength –

Positive-Sum: The Power of “And”

Change the paradigm from

the dated zero-sum (win/win)

to a “positive-sum” model:

Create a win/win scenario,

not an either/or (vs.)

involving unnecessary trade-offs

and false dichotomies …

Privacy by Design:

The 7 Foundational Principles

1. Proactive not Reactive:

Preventative, not Remedial; 2. Privacy as the Default setting; 3. Privacy Embedded into Design;

4. Full Functionality:

Positive-Sum, not Zero-Sum; 5. End-to-End Security:

Full Lifecycle Protection;

6. Visibility and Transparency: Keep it Open;

7. Respect for User Privacy: Keep it User-Centric.

“Privacy by Design is considered one of the most important concepts by members of the Japanese Information Processing Development Center … We have heard from Japan’s private sector

companies that we need to insist on the principle of Positive-Sum, not Zero-Sum and become

enlightened with Privacy by Design.”

— Tamotsu Nomura, Japan Information Processing Development Center, May 28, 2014

Operationalizing Privacy by Design

9 PbD Application Areas

• CCTV/Surveillance cameras in mass transit systems;

• Biometrics used in casinos and gaming facilities;

• Smart Meters and the Smart Grid; • Mobile Communications;

• Near Field Communications; • RFIDs and sensor technologies; • Redesigning IP Geolocation; • Remote Home Health Care; • Big Data and Data Analytics.

Do NOT focus exclusively on the

“uses” of personal data

Zero-Sum Prevails:

Privacy Paternalism

“ Leaving it up to companies and governments to determine the acceptable secondary uses of personal data is a flawed proposition, that will no doubt lead to

greater privacy infraction. If the history of privacy has taught us anything, it is that an individual’s loss of control over their personal data leads to greater privacy

abuses, not fewer.”

The Veil of Privacy

“A regime that only pays attention to use erects

a Potemkin Village of privacy. From a distance, it

looks sound. But living within it we will find no

shelter from the sun or rain.”

– Professor Chris Hoofnagle

The Potemkinism of Privacy Pragmatism

Slate.com

http://www.slate.com/articles/technology/future_tense/2014/09/data_use_r egulation_the_libertarian_push_behind_a_new_take_on_privacy.html

Privacy Paternalism

“The authors fully agree that accountability should be strengthened, but disagree with the proposal to

weaken critical FIPPs and diminishing the role of the individual … Diminishing limits on specified purposes, collection and uses of personal data minimizes rather

than strengthens accountability.”

OECD Privacy Principles

(Fair Information Practices)

1. Collection Limitation 2. Data Quality 3. Purpose Specification 4. Use Limitation 5. Security Safeguards 6. Openness 7. Individual Participation 8. Accountability Revised July, 2013

Big Data

• 90% of all data was created within the last 2 years;

• Big Data analysis and data analytics promise new

opportunities to gain valuable insights and benefits

– new predictive modes of analysis;

• But, it will also enable expanded surveillance,

increasing the risk of unauthorized use and

First, Comes

the Hype

The Hype Phase:

• Big Data will rule the world!

• Everything else (including privacy)

must step aside;

Then, the

Big Data Technology is Not Foolproof

“Despite rampant interest from enterprise

leaders and often sizeable investments in

Big Data technologies, many programs still

sputter or fail completely.”

— Evanta Leadership Network,

Some People are Now Asking:

Is Big Data a Big Mistake?

• The Big Data that interests many companies is

what we might call “found data” – the digital

exhaust of web searches, credit card payments

and mobiles pinging the nearest phone mast;

• Such data sets are cheap to collect relative to their

size – a messy collage of data-points, collected for

disparate purposes;

• But, how good is the data?

Big Data is moving from its

“inflated expectations” phase

to a “trough of disillusionment.”

— Gartner Hype Cycle, April, 2014

MIT Big Data Expert

Calls for Privacy

“MIT Professor Alex Pentland has proposed a

‘New Deal on Data,’ which calls for individuals

to own their data and control how it is used

and distributed.”

— Measuring Idea Flows to Accelerate Innovation, New York Times, April 15, 2014.

“But while big data promise much to scientists,

entrepreneurs and governments, they are doomed

to disappoint us if we ignore some very familiar

statistical lessons. There are a lot of small data

problems that occur in big data. They don’t

disappear because you’ve got lots of the stuff …

they get worse!”

Winton Professor, Cambridge University

— Big data: are we making a big mistake?

FT Magazine, March 2014.

“Forget Big Data …

what is needed is

Good Data”

— Barrie McKenna,

The serious economic cost of Canada's data deficit, Globe and Mail, May 12, 2014

2013 Data Scientists Conference

88% of the Data Scientists surveyed said

that consumers should worry about the

privacy issues associated with Big Data

Context is Key

• Performing data analytics on context-free data

will only yield correlations (which at times, will

be spurious);

• By adding context as a feature in the analytics,

we may be able to impute causality – which has

the potential to be invaluable in our analyses.

Privacy Breeds Innovation:

It Does NOT Stifle It!

• The argument that privacy stifles innovation reflects a dated, zero-sum mindset;

• The notion that privacy must be sacrificed for innovation is a false win/lose dichotomy, consisting of unnecessary trade-offs;

• The opposite is true – privacy drives innovation – it forces innovators to think creatively to find solutions that will serve multiple functionalities;

• We need to abandon zero-sum thinking and adopt a positive-sum paradigm where both innovation and privacy may be achieved – we need a new playbook!

Privacy by Design and the

Internet Engineering Task Force (IETF)

“The concept of Privacy by Design has gotten a lot

of attention over the past few years and within the

IETF we have tried to investigate how we can

consider privacy in the design of protocols and

architectural designs in a more systematic way.”

— Privacy Considerations for Internet Protocols, Internet Engineering Task Force (IETF), www.ietf.org

Carnegie Mellon University –

Privacy By Design

• Master's degree program for privacy engineers to be offered by Carnegie Mellon University, School of

Computer Science;

• The Master of Science in Information Technology-Privacy (MSIT-Privacy) is a 12-month program that began in the fall of 2013;

• The program will emphasize the concept of Privacy by

Design, in which safeguards are incorporated into the

design of systems and products from the very beginning of the development process.

OASIS Technical Committee –

Privacy by Design for Software Engineers

• Commissioner Cavoukian and Professor Jutla are the Co-Chairs of a new technical committee (TC) of OASIS

“PbD-SE (software engineers) TC;”

• The purpose of PbD-SE is to provide PbD governance and documentation for software engineers; and

• The PbD standards developed will pave the way for software engineers to code for Privacy, by Design.

OASIS and Privacy by Design

• 2014 – the OASIS PbD-SE Technical Committee (TC) approved the

Privacy by Design Documentation for Software Engineers Version 1.0 as a Committee Specification Draft (CSD), and the Annex Guide to Privacy by Design Documentation for Software Engineers

Version 1.0 as a Committee Note Draft (CND);

• This vote represents a milestone for the PbD-SE TC, acknowledging the substantial progress that has been made over the last year;

• The PbD-SE TC will undertake another review cycle before submitting the CSD and CND to public review.

— Commissioner Cavoukian

“Privacy is just as Big as Big Data. The tools exist to systemically protect personal information and bring about the benefits of Big Data.

Together we can ensure that Big Data and ‘Big Privacy’ can both be accomplished to enable win-win scenario.”

“There are considerable

risks in abandoning

de-identification efforts,

including the fact that

individuals and

organizations may simply

cease disclosing

de-identified information for

secondary purposes, even

those seen to be in the

public interest.”

Proposed Approach to Internet of Things

Data Security

1. Security by Design

– Build security into devices from the outset;

2. Data Minimization

– Data which isn’t collected can’t fall into the wrong hands;

3. Notice and choice for unexpected uses

– Consumers should be given clear, simple notices of how their data will be used, along with a consent mechanism.

Edith Ramirez – US FTC chairwoman CES 2015

Privacy is

Good for Business

Consumer Choice and Privacy

• There is a strong competitive advantage for businesses to invest in good data privacy and security practices; • “A significant portion of the population is becoming

concerned about identity theft, and it is influencing their purchasing decisions.”

— Rena Mears, Deloitte & Touche,

Survey Reports An Increase in ID Theft and Decrease in Consumer Confidence.

The Bottom Line

Privacy should be viewed as a

business issue, not a

compliance issue

Think strategically and transform privacy into a

competitive business advantage

Cost of Taking the Reactive Approach

to Privacy Breaches

Proactive

Reactive

Loss of Consumer Confidence and Trust

First “Privacy Marketplace” at the

International Consumer Electronics Show

in Vegas

“ Privacy is a hot issue right now. It’s on everyone’s radar … Consumers asking about privacy – that was the big takeaway. These companies in the privacy marketplace, in large part aren’t advocates. They’re entrepreneurs looking to capitalize on market

opportunity. They expect a larger privacy marketplace next year and for brands to incorporate “privacy” into their marketing…

Anyone, everyone, can understand the need for privacy.”

Victor Cocchia CEO, Vysk Speaking at CES: Jan, 2015

Success in the Future will Require Positive-Sum

Paradigms

1. Big Data and privacy are not mutually exclusive:

• Data is one of the most valuable assets of any organization ;

• Privacy is about personally identifiable information;

• Consumer demands are creating additional pressures;

2. Proactive privacy drives innovation:

• It is entirely possible to achieve privacy in the Big Data era, while also using data analytics to unlock new insights and innovations to move an organization forward;

3. Innovation and privacy: You can have it all:

• Organizations will continue to apply data analytics to Big Data in order to advance their strategic goals and better serve their customers.

— Commissioner Cavoukian,

SmartData:

Privacy by Design 2.0

The Next Evolution in Data Protection:

“SmartData”

Developed by Dr. George Tomko, at the Identity, Privacy and Security Institute, University of Toronto, SmartData

represents privacy in the future with greater control of personal information.

Intelligent “smart agents” to be introduced into IT systems virtually – thereby creating “SmartData,” – a new approach to Artificial

SmartData:

It’s All About User Control

It’s All About Context:

• Evolving virtual cognitive agents that can act as your proxy to protect your personally identifiable data;

Intelligent agents will be evolved to:

• Protect and secure your personal information;

• Disclose your information only when your personal criteria for release have been met;

• Put the user firmly in control –

Methods of Creating Intelligent Agents

• Top-down, rule-based design (traditional AI);

• Bottom-up “evolutionary robotics design;”

• The combination of a top-down and

bottom-up hybrid will yield the most

dynamic results.

Southern Ontario Smart Computing

Innovation Platform (SOSCIP)

“SOSCIP is a groundbreaking research collaboration involving seven leading southern Ontario universities, IBM Canada, and small- and

medium-sized enterprises (SMEs) across the province.”

Ryerson’s Privacy & Big Data Institute proposal involving SmartData received SOSCIP approval to explore the feasibility of privacy-protective monitoring

of health-related outbreaks, using a foundation of intelligent virtual agents as envisioned in SmartData.

A New Approach:

Applying Privacy by Design

to Surveillance

“As long as the threat of terrorism exists and the global conditions that instantiate those threats continue, effective measures will be needed to counteract terrorism.

At the same time, in order for a free and open society to function properly, privacy and civil liberties must be strongly protected.”

• A new system of surveillance, which enables

effective counter-terrorism measures to be pursued – in a privacy-protective manner;

• The underlying technology builds on Artificial Intelligence, advances in cryptography involving

Homomorphic Encryption, and Probabilistic Graphical Models (involving Bayesian Networks).

Introducing PPS:

Summary of PPS

Privacy Protective Surveillance is a positive-sum, “win-win”

alternative to current counter-terrorism surveillance systems. It incorporates two primary objectives in its design:

1. An AI system consisting of feature detection that scans the Web and related databases using a “blind-sight” procedure to detect digital evidence relating to potentially suspicious terrorist activity by some, without infringing on the privacy of unrelated individuals;

2. A technological infrastructure to ensure that any personally

identifying information (“PII”) on unsuspected individuals is not collected and, in those associated with targeted activity, encrypted PII will only be divulged with judicial authorization (a warrant issued by the court).

Concluding Thoughts

• Privacy risks are best managed by proactively embedding the principles of Privacy by Design – prevent the harm from arising – avoid the data breach;

• Focus on prevention: It is much easier and far more cost-effective to build in privacy, up-front, rather than after-the-fact;

• Abandon zero-sum thinking – embrace doubly-enabling systems: Big Data and Big Privacy;

• Get smart – lead with Privacy – by Design, not privacy by chance or, worse, Privacy by Disaster!

Contact Information

Ann Cavoukian, Ph.D.

Executive Director

Privacy and Big Data Institute Ryerson University 285 Victoria Street Toronto, Ontario M5B 2K3 Phone: (416) 979-5000 ext. 3138 [email protected] [email protected] twitter.com/PrivacyBigData