The Future of Privacy

Blair Reeves Product Manager, IBM Digital Analytics

Aurelie Pols

Chief Visionary Officer, Mind Your Privacy

@BlairReeves

@AureliePols

@BlairReeves

Privacy is Perception

… but do another.

66% of Americans say they do not want to receive targeted ads

53% of Americans want websites they visit to offer discounts tailored to their interests

64% of Americans say they are less likely to vote for a political candidate who buys information about their online behavior

92% of U.S. internet users say they worry about privacy online

Behaviorally-targeted ads have 240%+ higher conversion rates

80% of internet users do not “always” read privacy policies, and only half bother logging out

Privacy is Perception

What  informa,on  am  I  giving  away?   Do  I  

know?  

Do  I  care?  

User-supplied: •  Name •  Date of birth •  Sex •  Location (City, State)

Inferred: •  Mobile device type •  Login frequency •  Clickstream •  Browsing history •  Purchase history •  Social connections •  Etc.

@BlairReeves

Consumers rely more and more on free cloud services

@BlairReeves

0

200,000,000

400,000,000

600,000,000

800,000,000

1,000,000,000

1,200,000,000

1,400,000,000

Search Gmail Google Plus Drive

Google Services MAUs

Extrapolated

Confirmed by Google

What the future looks like

@BlairReeves

@BlairReeves

More and more of our lives will be lived digitally

Cloud ● Mobile ● Connected

Citizens ● Consumers ● Humans

About me

Aurélie  Pols  Chief  Visionary  Officer  Mind  Your  Privacy  

•  Grew up in the Netherlands, Dutch passport •  French mother tongue •  Most of my friends are bilingual at least •  Have Polish & Russian origins •  Set-up my 1st start-up in Belgium in 2003 •  Sold it to Digitas LBi (Publicis), in 2008 •  Moved to Spain in 2009 •  Created 2 other start-ups in Spain in 2012

Mind Your Group, Putting Your Data to Work Mind Your Privacy, Data Science Protected

Yes, a “law firm” but we prefer to say

a bunch of Data Scientists working with a bunch of Lawyers

@AureliePols

Context: Privacy tri-partite

Joint effort by: 1.  Governments &/or international

Associations => legislation, guidelines, …

2.  Citizens/voters/consumers 3.  Businesses

Each party wanting to defend: o  Personal Data Protection & the

Rule of Law through respect of Fundamental Rights

vs. o  Profits & hopefully

Sustainability

Governments

Citizens/voters/

consumers

OUR GLOBAL SOCIETY

Businesses

Analytics vendors / Agencies / Data Users

@AureliePols

About Mind Your Privacy

 Boutique consultancy firm providing security consultancy services and legal Privacy advice

 Our typical international clients manage sensitive data within an international landscape

 Pluricultural and multi-skilled profiles - legal, data scientists and technical

 Providing complete solutions to complex data and privacy issues

@AureliePols

This presentation is for Data Users

Source: http://ochuko.files.wordpress.com/2010/04/sides-of-a-coin.jpg

@AureliePols

Privacy, the Word

From our Wikipedia friends: From Latin: privatus "separated from the rest, deprived of something, esp. office, participation in the government", from privo "to deprive” The ability of an individual or group to seclude themselves or information about themselves and thereby express themselves selectively. The boundaries and content of what is considered private differ among cultures and individuals, but share common themes. When something is private to a person, it usually means there is something to them inherently special or sensitive. The domain of privacy partially overlaps security, including for instance the concepts of appropriate use, as well as protection of information. Privacy may also take the form of bodily integrity.

Source: https://en.wikipedia.org/wiki/Privacy

@AureliePols

Privacy, nothing to hide?

“If you have something that you don’t want anyone to know, maybe you shouldn’t be doing it in the first place.” Eric Schmidt, 2009 https://www.youtube.com/watch?v=A6e7wfDHzew

Tip: Follow Daniel Solove on LindedIn!

@AureliePols

An Anglo-Saxon term?

Source: http://web.mit.edu/bigdata-priv/

http://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_may_1_2014.pdf

@AureliePols

Blame?

Source: http://mobile.nytimes.com/blogs/bits/2014/05/05/white-house-tech-advisers-online-privacy-is-a-market-failure/

@AureliePols

Solution?

@AureliePols

Is this complicated?

Source: https://www.forrestertools.com/heatmap/

@AureliePols

Regulatory law

“Every country is a little different. You run into different regulatory regimes and you need to make sure you have the right tools so that people can implement the right policies they are required to by law… They aren’t that different”

Source: Bloomberg Singapore Sessions April 23rd 2014 http://www.bloomberg.com/video/big-data-big-results-singapore-sessions-4-23-kHN5zrGbR_Wq6hbmV9~aXQ.html

@AureliePols

A global perspective US & UK EU APEC

Common Law Continental Law Continental law influenced

Class actions Fines (by DPAs: Data Protection Agencies)

Privacy Personal Data Protection (PDP) Business focused Citizen focused: data belongs to the

visitor/prospect/consumer/citizen Patchwork of sector based legislations: HIPPA, COPPA, VPPA, …

Over-arching EU Directives & Regulations

PII: varies per state Risk levels: low, medium, high, extremely high

@AureliePols

Democracy & the rule of law US & UK EU APEC

Common Law Continental Law Continental law influenced

Class actions Fines (by DPAs: Data Protection Agencies)

Privacy Personal Data Protection (PDP)

Business focused Citizen focused: data belongs to the visitor/prospect/consumer/citizen

Patchwork of sector based legislations: HIPPA, COPPA, VPPA, …

Over-arching EU Directives & Regulations

PII: varies per state Risk levels: low, medium, high, extremely high

@AureliePols

Data Protection

In light of fuzzy interpretations of Privacy, could we agree upon • Thinking of it as data protection • Protecting the data we are entrusted with • While respecting the Right to “Privacy” • Taking into consideration information security measures

@AureliePols

Democracy & the rule of law US & UK EU APEC

Common Law Continental Law Continental law influenced

Class actions Fines (by DPAs: Data Protection Agencies)

Privacy Personal Data Protection (PDP) Business focused Citizen focused: data belongs to the

visitor/prospect/consumer/citizen Patchwork of sector based legislations: HIPPA, COPPA, VPPA, …

Over-arching EU Directives & Regulations

PII: varies per state

Risk levels: low, medium, high, extremely high

@AureliePols

PII: ah but we don’t collect it!

Medical information as PII California Arkansas Missouri New Hampshire North Dakota Texas Virginia

Financial information as PII Alaska North Carolina Iowa North Dakota Kansas Oregon Massachusetts South Carolina Missouri Vermont Nevada Wisconsin New York* Wyoming

Passwords as PII Georgia Maine Nebraska

Biometric information as PII Iowa Nebraska North Carolina Wisconsin

Source: information based on current ongoing analysis (partial results) @AureliePols

So what is considered PII?

Personal Information (based on the definition commonly used by most US states)

i Name, such as full name, maiden name, mother‘s maiden name, or alias ii Personal identification number, such as social security number (SSN),

passport number, driver‘s license number, account and credit card number iii Address information, such as street address or email address iv Asset information, such as Internet Protocol (IP) or Media Access Control

(MAC) v Telephone numbers, including mobile, business, and personal numbers.

Information identifying personally owned property, such as vehicle registration number or title number and related information

Source: information based on current ongoing analysis (partial results)

@AureliePols

If you collect PII… then

US & UK EU APEC Common Law Continental Law Continental

law influenced

Class actions Fines (by DPAs: Data Protection Agencies)

Privacy Personal Data Protection (PDP) Business focused Citizen focused

Patchwork of sector based legislations: HIPPA, COPPA, VPPA, …

Over-arching EU Directives & Regulations

PII: varies per state

Risk levels: low, medium, high, extremely high

@AureliePols

PII & legislation questions

•  Who knows their Chief Privacy Officer? According to the DMA (US), CMOs should abide to an average # of 300 pieces of legislation •  Is PII really PII? Zip code + gender + date of birth can uniquely identify 87% of the US population

Source: Microsoft Latanya Sweeney (2000) http://dataprivacylab.org/projects/identifiability/paper1.pdf

@AureliePols

PII vs. Risk levels

Low

Medium (profiling)

High (sensitive)

Risk level

Data type Information Security Measures

Extremely high (profiling of sensitive data)

PII

@AureliePols

Data lifecycles

Analytics => Follow the Money

Information Security & Compliance => Follow the Data

@AureliePols

The Privacy framework 1

User consent

Fair & Legal process: FIPPs

Information for approved use

Data diving analysis / Big Data

New business opportunity through

data

Purpose

@AureliePols

The Privacy framework 2

User consent

Fair & Legal process: FIPPs

Information for approved use

Data diving analysis / Big Data

New business opportunity through

data

Purpose

@AureliePols

Fair Information Practice Principles - FIPPs

Source: https://security.berkeley.edu/sites/default/files/uploads/FIPPSimage.jpg

@AureliePols

Data collection

•  Purpose – Consent o  Reason for data collection:

•  Website improvement, better User Experience •  Marketing communication

•  Opt-in? Opt-out? Double opt-in? o  Depends upon:

•  Type of data: PII, sensitive data •  Type of sector: financial, health, … •  Geography: US vs. EU vs. ???

@AureliePols

Examples: US vs. Spain

US: no purpose, no consent

Spain: consent, purpose, opt-in & opt-out

@AureliePols

Trust & creepiness

Consent is about a reasonable expectation of the use of data o  There’s a fine line

between feeling charmed vs. feeling invaded

o  Create win-win situations: •  Customers give company information •  Customers get better service/value for money

@AureliePols

Consent & Trust for Telcos

Slide borrowed from Stephen John Deadman from Vodafone Group Services Limited, IAPP congress Brussels, November 2013

@AureliePols

Typical personal data misconceptions

Very often present in technology companies o  We do not identify the user while using the data, so we have no

issues with Privacy law o  We only use the serial # of the users device, so the data is

anonymous and we have no issues with Privacy laws o  We encrypt the data so we are no longer using/sending/receiving

personal data o  We use hashes to replace all serial #, so the data is now

anonymous and we have no issues with Privacy laws o  We anonymize the data, so we are not using personal data o  We can use the user’s data for anything we want, as long as we

keep the data to ourselves o  Look: big name companies are doing the same, so we are ok

Slide borrowed from @simonhania from TomTom, IAPP congress Brussels, November 2013

@AureliePols

EU fines? Spain: responsible for 80% of data protection fines in the EU

Source: http://i0.kym-cdn.com/photos/images/newsfeed/000/242/381/63a.jpg

Source: http://www.mindyourprivacy.com/download/privacy-infographic.pdf

@AureliePols

Security (technical)

Data Collection

Proc

esse

s Resources

security

@AureliePols

Who has access?

Source: Mind Your Privacy seal, specific audit for analytics tools & data agencies

@AureliePols

Supplier reviews - Cloud Typical international company set-up

Cloud: •  SaaS •  PaaS •  IaaS

@AureliePols

Data flows = shared responsibility

Source: http://cdn2-b.examiner.com/sites/default/files/styles/image_content_width/hash/6e/54/6e54dfaa644b1fe589e4462b6f2a20b7.jpeg?itok=OIAVYOR1

@AureliePols

As secure as the weakest link

Source: http://www.lebsontech.com/images/ChainLight.jpg

@AureliePols

WHERE TO START?

@AureliePols

Balancing Risks & Benefits

Risks   SaaS PIAs: Privacy

Impact Assessment   Security evaluation of

your own information   Nature of your own

data

Benefits  Price  Transfer of

responsibility?  Availability (BYOD,

strike, natural disaster, …)

Source: http://www.labeshops.com/image/cache/data/summitcollection/7918l-lady-justice-3-feet-statue-800x800.jpg

@AureliePols

Compliance vs. Risk Assessments •  Achieving 100% compliance is a chimera

o  Compliance is a journey, not a destination o  Level of required compliance linked to

•  Sector •  Personal internal management •  Company risk profile

•  Risk is a moving target o  Risk of being fined o  Risk of being breached o  Brand perception => subjective

@AureliePols

A simple example

PII viewer for Google Analytics http://davidsimpson.me/pii-viewer-for-google-analytics/

Customer DB Data Collection

Data Visualization

  Privacy Policy   Hosting   Security   Terms of Use   Access

  Consent   FIPPs   Data

retention period

  (Hosting)   Security   Access

What data is Chrome sending? Is your company accountable?

@AureliePols

Other ex.: BBVA Commerce 360

26M transactions/day 25% of marketshare for Spain

Source: http://www.slideshare.net/cibbva/juan-carlos-plaza-explica-los-proyectos-sobre-big-data-de-bbva

@AureliePols

Data transformations

  Consent & purpose   Through which pipes?   Data (transfer) security?   Data access?   …

From granular to aggregated

@AureliePols

What to do?

1.  Know your information structure (cloud) o  Can you exactly draw the Cloud supplier slide?

2.  Cloud inventory (PIA) o  Provider (& sub-contractors) o  Location

•  Cloud service HQ •  Servers

•  Applicable law: our friend Snowden •  Physical location: earthquakes?

•  Any incidents to report? •  In-house control access (risk) •  Terms & Conditions

•  Information Security measures •  Related to Privacy

@AureliePols

What to do?

3.  Know your Data structure: data inventory (cloud) o  (Do you know which data can be found where)? o  Have you reviewed your information security measures? o  What happens in case of a breach?

4.  Authorization required? o  Approval International Data Transfers (IDT) o  Safe Harbor o  Binding Corporate Rules (BCR) o  User consent

@AureliePols

Moving to the cloud

1.  List your departments 2.  What type of data needs to be moved? 3.  What are your data risk levels?

o  Low / Medium / High / Extremely High

4.  What do you need for compliance?

Have a list of questions ready to ask your cloud provider except for the price!

@AureliePols

Note: slides blurred for confidentiality reasons

@AureliePols

Note: slides blurred for confidentiality reasons

@AureliePols

MYP Information Security Framework

@AureliePols

MYP Services

For Data Users   Risk Assessment to define maturity model (COBIT) and roadmap   Define processes to establish proper security measures and create

policies to structure these process   Audit the level of compliance of security measures that are in place   Train staff to align them with security plan while reducing the risk of

suffering a data breach   Define KPIs to adequately deploy a data governance program

@AureliePols

MYP Services

Analytics SaaS Providers   Advice during the procurement process to define the best provider in

terms of data security management and privacy compliance   Audit providers´ management of data and privacy

For Analytics vendors & agencies

 PrivacyGreen Seal

THANKS For listening

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