smarter comm"the future of privacy". aurélie pols at ibm smarter commerce global summit...
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In a data driven economy, analysts must be concerned with how data is collected, processed and subsequently used to improve online customer experiences, during those moments that matter. Unlocking Value & Controlling Risk by #MindYourPrivacyTRANSCRIPT
#smartercommerce
Aurélie PolsCo-founder & Chief Visionary Officer
Mind Your Privacy & Mind Your [email protected]
@aureliepols
The Future of PrivacyData is the New Oil, Privacy is the New GreenUnlocking Value & Controlling Risk
@AureliePols
About me
Aurélie PolsChief Visionary OfficerMind 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 WorkMind 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-partiteJoint effort by:
1. Governments &/or international Associations => legislation, guidelines, …
2. Citizens/voters/consumers3. Businesses
Each party wanting to defend: – Personal Data Protection & the Rule of
Law through respect of Fundamental Rights vs.
– 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
If you've got nothing to hide,
you've got nothing to fear!
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 2014http://www.bloomberg.com/video/big-data-big-results-singapore-sessions-4-23-kHN5zrGbR_Wq6hbmV9~aXQ.html
@AureliePols
A global perspectiveUS & 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/citizenPatchwork 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 lawUS & 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/citizenPatchwork 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 lawUS & 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/citizenPatchwork 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… thenUS & 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 populationSource: Microsoft Latanya Sweeney (2000) http://dataprivacylab.org/projects/identifiability/paper1.pdf
@AureliePols
PII vs. Risk levels
Low
Medium(profiling)
High(sensitive)
Risk level
Data typeInformation 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– Reason for data collection: • Website improvement, better User Experience• Marketing communication
• Opt-in? Opt-out? Double opt-in?– 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– There’s a fine line
between feeling charmed vs. feeling invaded
– 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– We do not identify the user while using the data, so we have no
issues with Privacy law– We only use the serial # of the users device, so the data is
anonymous and we have no issues with Privacy laws– We encrypt the data so we are no longer using/sending/receiving
personal data– We use hashes to replace all serial #, so the data is now
anonymous and we have no issues with Privacy laws– We anonymize the data, so we are not using personal data– We can use the user’s data for anything we want, as long as we
keep the data to ourselves– 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
TechnologicalPr
oces
ses Resources
security
@AureliePols
Who has access?
Source: Mind Your Privacy seal, specific audit for analytics tools & data agencies
@AureliePols
Supplier reviews - CloudTypical 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
BenefitsPriceTransfer 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– Compliance is a journey, not a destination– Level of required compliance linked to
• Sector• Personal internal management• Company risk profile
• Risk is a moving target– Risk of being fined– Risk of being breached– Brand perception => subjective
@AureliePols
A simple examplePII viewer for Google Analyticshttp://davidsimpson.me/pii-viewer-for-google-analytics/
Customer DBData 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)– Can you exactly draw the Cloud supplier slide?
2. Cloud inventory (PIA)– Provider (& sub-contractors)– 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)– (Do you know which data can be found where)?– Have you reviewed your information security
measures?– What happens in case of a breach?
4. Authorization required?– Approval International Data Transfers (IDT)– Safe Harbor– Binding Corporate Rules (BCR)– User consent
@AureliePols
Moving to the cloud1. List your departments2. What type of data needs to be moved?3. What are your data risk levels?– 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 ServicesFor 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 ServicesAnalytics 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 & agenciesWEMindYourPrivacy Seal
THANKSFor listening
Aurélie PolsCo-founder & Chief Visionary Officer
Mind Your Privacy & Mind Your [email protected]@aureliepols
Privacy in Digital Marketing:Regulatory Threats vs. Data OpportunitiesBerlin - June 2nd 2014 http://digitalanalyticshub.com/berlin2014/workshops/#ND68
Next full day workshop