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The Decade of Privacy by Design
The Decade of Privacy by Design
Adoption of “Privacy by Design” as an International Standard
Adoption of “Privacy by Design” as an International Standard
Privacy by Design: The 7 Foundational Principles
Privacy by Design: The 7 Foundational Principles
Operationalizing Privacy by Design
Operationalizing Privacy by Design
Cost of Taking the Reactive Approach to Privacy Breaches
Cost of Taking the Reactive Approach to Privacy Breaches
“Privacy is just as Big as Big Data
“Privacy is just as Big as Big Data
“There are considerable risks in abandoning de-identification efforts,
“There are considerable risks in abandoning de-identification efforts,
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Data Governance: Addressing the Big Data Challenge

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1Data Governance: Addressing the Big 17paradigm where both innovation and privacy
Data Challenge. Ann Cavoukian, Ph.D. may be achieved – we need a new playbook!
Executive Director Privacy and Big Data 18“Privacy is just as Big as Big Data.
Institute Ryerson University. Information The tools exist to systemically protect
Technology Law Spring Forum Toronto, personal information and bring about the
Ontario May 4, 2015. benefits of Big Data. Together we can
2The Decade of Privacy by Design. ensure that Big Data and ‘Big Privacy’ can
3Adoption of “Privacy by Design” as an both be accomplished to enable win-win
International Standard. Landmark scenario.”. — Commissioner Cavoukian.
Resolution Passed to Preserve the Future 19“There are considerable risks in
of Privacy By Anna Ohlden – October 29th abandoning de-identification efforts,
2010 - including the fact that individuals and
http://www.science20.com/newswire/landmark organizations may simply cease disclosing
resolution_passed_preserve_future_privacy de-identified information for secondary
JERUSALEM, October 29, 2010 – A landmark purposes, even those seen to be in the
Resolution by Ontario's Information and public interest.”. — Commissioner
Privacy Commissioner, Dr. Ann Cavoukian, Cavoukian.
was approved by international Data 20Internet of Things (IoT).
Protection and Privacy Commissioners in 21Internet of Things: Three Broad
Jerusalem today at their annual Categories. 1) Wearable Computing:
conference. The resolution recognizes Everyday objects i.e. Google glass, Apple
Commissioner Cavoukian's concept of watch 2) Quantified Self: Record
Privacy by Design - which ensures that information about one’s habits, lifestyle
privacy is embedded into new technologies and activities i.e. Fitness and sleep
and business practices, right from the trackers 3) Home Automation: Computer
outset - as an essential component of controlled thermostats, light bulbs etc.
fundamental privacy protection. Full 22Internet of Things: Privacy Risks.
Article: Third party monitoring removes control of
http://www.science20.com/newswire/landmark one’s information from the individual
resolution_passed_preserve_future_privacy. involved; The nature of the devices may
4Privacy by Design: Proactive in 37 make it more difficult to obtain consent
Languages! English French German Spanish before data collection begins; Specific
Italian Czech Dutch Estonian Hebrew Hindi instances of data collection may not seem
Chinese Japanese. 13.Arabic 14.Armenian important on their own, but when
15.Ukrainian 16.Korean 17.Russian aggregated, they can create a
18.Romanian 19.Portuguese 20.Maltese comprehensive picture of a person that may
21.Greek 22.Macedonian 23.Bulgarian 24. be extremely harmful to the individuals
Croatian 25.Polish. 26.Turkish involved, especially in the hands of
27.Malaysian 28.Indonesian 29.Danish unauthorized third parties.
30.Hungarian 31.Norwegian 32.Serbian 23EU Article 29 Working Party.
33.Lithuanian 34.Farsi 35.Finnish Recommendations on the Internet of Things:
36.Albanian 37.Catalan. Make privacy the default setting … follow
5Abandon Zero-Sum (Win/Lose) Paradigms! Privacy by Design, delete all raw data
6replace “vs.” with “and”. Positive-Sum after processing; Respect a user’s
Model: The Power of “And”. Change the self-determination over their own data,
paradigm from a zero-sum to a and seek consent in a user-friendly way;
“positive-sum” model: Create a win-win Be transparent about how a user’s data is
scenario, not an either/or (vs.) involving being used; When sensors are continuously
unnecessary trade-offs and false collecting one’s personal data, remind
dichotomies … users of this surveillance activity;
7Privacy by Design: The 7 Foundational Ensure that data published to social
Principles. Proactive not Reactive: platforms remain private, by default;
Preventative, not Remedial; Privacy as the Users should not be penalized for failing
Default setting; Privacy Embedded into to consent; Data should be De-Identified,
Design; Full Functionality: Positive-Sum, except when necessary.
not Zero-Sum; End-to-End Security: Full 24Privacy Commissioners Declaration.
Lifecycle Protection; Visibility and 36th Int’l Conference of Data Protection
Transparency: Keep it Open; Respect for and Privacy Commissioners The value of
User Privacy: Keep it User-Centric. Internet of Things (IoT) is not only in
www.ipc.on.ca/images/Resources/7foundation the devices, but in the services that
lprinciples.pdf. arise from their use; Connectivity is
8Operationalizing Privacy by Design. 9 ubiquitous: it is the joint responsibility
PbD Application Areas CCTV/Surveillance of all actors to ensure trust in connected
cameras in mass transit systems; systems : Transparency is Key; Protection
Biometrics used in casinos and gaming should begin from the moment data that is
facilities; Smart Meters and the Smart collected; “Privacy by Design should be
Grid; Mobile Communications; Near Field the key selling point of innovative
Communications; RFIDs and sensor technologies” Strong, active and
technologies; Redesigning IP Geolocation; constructive debate is necessary to
Remote Home Health Care; Big Data and Data overcome the huge challenges presented by
Analytics. the developers of IoT. -September, 2014
9Cost of Taking the Reactive Approach Mauritius.
to Privacy Breaches. Reactive. Proactive. 25Proposed Approach to Internet of
10Letter from JIPDEC – May 28, 2014. Things: Data Security. Security by Design
“Privacy by Design is considered one of Build security into devices from the
the most important concepts by members of outset; Data Minimization Data which isn’t
the Japanese Information Processing collected can’t fall into the wrong hands;
Development Center … We have heard from Notice and choice for unexpected uses
Japan’s private sector companies that we Consumers should be given clear, simple
need to insist on the principle of notices of how their data will be used,
Positive-Sum, not Zero-Sum and become along with a consent mechanism. Edith
enlightened with Privacy by Design.”. — Ramirez – US FTC chairwoman CES 2015.
Tamotsu Nomura, Japan Information 26There is an Essential Need to Embed
Processing Development Center, May 28, Privacy into IoT and Mobile Devices, by
2014. Design.
11Big Data. 27Privacy is Good for Business.
12Big Data. 90% of all data was created 28Privacy should be viewed as a business
within the last 2 years; Big Data analysis issue, not a compliance issue. The Bottom
and data analytics promise new Line. Think strategically and transform
opportunities to gain valuable insights privacy into a competitive business
and benefits – new predictive modes of advantage.
analysis; But, it will also enable 29The Argument that Privacy Stifles Big
expanded surveillance, increasing the risk Data Innovation Reflects a Dated, Zero-Sum
of unauthorized use and disclosure, on a Mindset. Big Data and privacy are not
scale previously unimaginable. mutually exclusive: Data is one of the
13Big Data Technology is Not Foolproof. most valuable assets of any organization ;
“Despite rampant interest from enterprise Privacy is about personal information;
leaders and often sizeable investments in Consumer demands are creating additional
Big Data technologies, many programs still pressures; Proactive privacy drives
sputter or fail completely.”. — Evanta innovation: It is entirely possible to
Leadership Network, May 29, 2014. achieve privacy in the Big Data era, while
14Big Data: More Than Just Input. “In also using data analytics to unlock new
the afterglow of Big Data’s buzz, many insights and innovations to move an
organizations are finding that successful organization forward; Innovation and
programs require much more than simply privacy: You can have it all:
plugging data into a program.”. — Evanta Organizations will continue to apply data
Leadership Network, May 29, 2014. analytics to Big Data in order to advance
15Big Data is moving from its inflated their strategic goals and better serve
expectations phase to a trough of their customers. — Commissioner Cavoukian,
disillusionment. — Gartner Hype Cycle, Using Privacy by Design to achieve Big
April 2014. Data Innovation Without Compromising
16Context is Key. Performing data Privacy.
analytics on context-free data will only 30Concluding Thoughts. Privacy risks are
yield correlations (which at times, will best managed by proactively embedding the
be spurious); By adding context as a principles of Privacy by Design – prevent
feature in the analytics, we may be able the harm from arising – avoid the data
to impute causality – which has the breach; Focus on prevention: It is much
potential to be invaluable in our easier and far more cost-effective to
analyses. build in privacy, up-front, rather than
17Privacy Breeds Innovation: It Does NOT after-the-fact; Abandon zero-sum thinking
Stifle It! The argument that privacy – embrace doubly-enabling systems: Big
stifles innovation reflects a dated, Data and Big Privacy: Yes, we can; Get
zero-sum mindset; The notion that privacy smart – lead with Privacy – by Design, not
must be sacrificed for innovation is a privacy by chance or, worse, Privacy by
false win/lose dichotomy, consisting of Disaster!
unnecessary trade-offs; The opposite is 31Contact Information. Ann Cavoukian,
true – privacy drives innovation – it Ph.D. Executive Director Privacy & Big
forces innovators to think creatively to Data Institute Ryerson University 285
find solutions that will serve multiple Victoria Street Toronto, Ontario M5B 2K3
functionalities; We need to abandon Phone: (416) 979-5000 x 3138
zero-sum thinking and adopt a positive-sum ann.cavoukian@ryerson.ca.
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