The Future of Privacy
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Original Working Session content: The Future of Privacy
Outcomes / Statements
- Data minimazation is a best practice, but
its difficult to control it’s difficult to enforce, because there is no general exact definition, what “minimization” means it can be bypassed using a broad formulated user consent we may loose this fight …
- Instead of enforce data minimazation we could invent a
collecting and selling personal data is a successful business model - therefore data minimazation is hard to enforce so: collecting data is NOT a misuse using data without a specific user-consent IS a misuse Correlation and / or merging of different data sources IS a misuse future challenge: misuse cases of specific data may change in future
- data anonymization is a best practice, but
big data analysis of combined data-sets may enable a re-personalization of previously anonymized data in case of a secure, effective (randomized) data anonymization there should be no restrictions for data collection
- Enforcing a consent-by-usage / consent-by-purpose model may be a part
of a solution
so: organizations are allowed to store the data, but they HAVE TO aks for a usage consent for any type of content at any time they want to use those data for a new purpose this consent has to have an defined expiration date
All data have to contain an individual time-of-expiration, were they have to be deleted automatically (auto-destroy mechanism) (except regulatory requirements force a later date of deletion)
How can we achieve that respecting privacy issues is seen as a business advantage and not a penalty? Which respect-privacy-incentives are possible?
- People are adviced to use fake-identities where ever possible!
Synopsis and Takeaways
“Is there a future for privacy?”
Wilhelm von Humboldt, 1791: “There is no freedom without security”
A.1 It’s not a legal question! Privacy as matter for individuals, not courts.
A.2 It’s not question of compliance (of companies, organizations, etc.)
A.3 It’s not a question of identifiability: we assume here that you ARE identifiable!
A.4 Review resources: are there resources for privacy which
- List types of privacy items - Deliver categorys of privacy
B.1 Types of privacy / personal data (brain storming)
|Including criticality (high||medium||low||none)|
- Name - Gender - Address - Email address - Phone numbers - Photos/Videos of person - Date of birth - Place of birth - Name of schools / universities / employers - Job-position - Salary - Property - Passport data - Biometric data, e.g., thumbprint - Social security number / health insurance ID - IP-Address - Cookies - Credit card numbers - Bank account numbers - Health data - DNA-profile - Live style data / tracking - Location data / movement profiles - Consumer data - Digital signatures - Digitally stored manual signatures (e.g., signature pads) - Criminal records - Political, religious or philosophical beliefs
B.2 Categories of privacy / personal data (brain storming)
Main categories: - Personal identifiable information (PII) - Sensitive personal information (SPI) [context dependend]
Sub categories: - Legally relevant data - Insurance relevant data - Socially relevant data - Financial data
Controls and Measures (Web Apps)
C.1 Browser technology: what should be improved (not: what is technical possible and not what vendors like to do)
C.2 Rules for apps: privacy by design
C.3 Automated information to individuals, not on request (e.g. once a year etc)
D.1 Are there technical solutions conceivable, which help individuals to collect
- Who has which type of personal data stored?
- Where is it stored?
This concerns “white hats”, that is, companies, organizations, and governments who have stored data.
The “black hats” (criminal individuals or gangs) are not in focus here.
(1) OWASP Summit 2011 Working Session “Privacy” ( https://www.owasp.org/index.php/Talk:Summit_2011_Working_Sessions/Session073 )
- Agenda and results: https://drive.google.com/file/d/0B1vROwh8vCBGWGR6VENqak9SaHc/view?usp=sharing
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