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http://toch.tau.ac.il/

Designing for privacy

Microsoft HertzeliaApril 2013

Department of Industrial Engineering

A Brief History of Privacy

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“the right to be let alone”

- Samuel D. Warren and Louis

D. Brandeis,

1890

וישא בלעם את עיניו וירא 'את ישראל ׁשכן לשבטיו'.

מה ראה? ראה שאין פתחיהן מכוונין זה לזה.

אמר: ראויין אלו שתשרה "שכינה ביניהן

100BC-300AC 1980

Controlling information and accessibility to others

- Ruth Gavison

Agenda

① Privacy disasters

② The mobile privacy landscape

③ Is privacy important?

④ The privacy toolbox

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1. Privacy Disasters

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What’s the worst that can happen?

Remember Google Buzz?

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Followers in Buzz

‣ Google suggested a list of followers to new users.

‣ The suggestions were the people who corresponded most with the user.

‣ By default, the list was open to the public and accessible through the user’s profile page.

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After 4 Days…

‣ Google had canceled the automatic follower list.

‣ And the removed Buzz’s public profile completely.

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After a Week…

‣ Law suits and FTC complaints were submitted.

‣ Users had abandoned Buzz quickly.

‣ Google had agreed to pay $8.5 Mil and was restricted considerably with regard to user data.

‣ Buzz was cancelled a year later.

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2. The Mobile Privacy Landscape

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Privacy Spheres in Mobile Computing

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Physical PrivacyInterference of the physical environment and attention

Data PrivacyCollecting and using information collected in the user’s action sphere

Information Threats

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‣ Can other people find where the person is?

‣ And physically threat the user or her property?

Identity Threats

‣ With only 4 locations of a person,

‣ and a census database,

‣ 95% of the population can be uniquely identified.

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Yves-Alexandre de Montjoye, César A. Hidalgo, Michel Verleysen & Vincent D. Blondel, Unique in the Crowd: The privacy bounds of human mobility, Nature 2013

Social Threats

‣ A location can tell about:

‣ What the user does

‣ Who the user meets

‣ Information is shared with the social network.

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Physical Privacy

The extent to which the phone interfere with the physical context of the user, draws the attention of the user or the environment.

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Vellux BeepersSounds and notifications

Concerns in Information Privacy

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Tsai, Janice, Patrick Kelley, Lorrie Cranor, and Norman Sadeh. "Location-sharing technologies: Privacy risks and controls." TPRC, 2009.

3. Is Privacy Important Anymore?

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“You already have zero privacy anyway. Get over it.”

Scott McNealySun Microsystems CEO

1999

Do Users Actually Care?

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Shoppers at a mall were offered $10 discount card - and an extra $2 discount if they agreed to share their shopping data. 50% declined the extra offer.

Source: The New York Times - http://www.nytimes.com/2013/03/31/technology/web-privacy-and-how-consumers-let-down-their-guard.html?smid=pl-share

But Wait…

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Shoppers were offered a $12 discount card and the option of trading it in for a $10 card to keep their shopping record private. 90% percent chose to trade privacy for $2.

Privacy is not Abstract Anymore

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Google Buzz Facebook Path

People care about concrete privacy threats, that impact their actual lives.

What do users actually do?

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Facebook users in an American University

Professional and Ethical Duty

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Legal Duty

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It is a Basic Human Need

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Its impossible live without a safe space for

experimentation, growth, and

personal expression

4. The Privacy Toolbox

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Types of Tools

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Policy-based Architecture-based

Pri

vacy

Gu

ara

nte

e

Notice

Choice

Access and Recourse

Data Minimization

Source: Marc Langheinrich. 2001. Privacy by Design - Principles of Privacy-Aware Ubiquitous Systems. In Proceedings of the 3rd international conference on Ubiquitous Computing (UbiComp '01),

‣ Be open with the user.

‣ Tell the user what happens to the data, at the right moment, and at the right context.

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Notice

What is a Good Notice?

‣ A good notice is a way that will enable the user to intelligently make a decision.

‣ We need to think: what is the default? What are the implications? Is there an undo?

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NoticeTell the user what happens to the data.

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Privacy as Part of the App Decision-Making Process. Patrick Gage Kelley, Lorrie Faith Cranor, and Norman Sadeh. CHI 2013.

http://cups.cs.cmu.edu/privacyLabel

‣ Provide the user with meaningful control over the information:

‣ Discriminative

‣ Easy to use

‣ Works out of the box

‣ A simple test should be: the data belongs to the user. Can she effectively exercise her ownership?

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Choice

Discriminative Control

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http://ie.microsoft.com/testdrive/browser/donottrack/

The Do Not Track (DNT) header requests that a web application disable either its tracking or cross-site user tracking.

Do Not Track

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http://ie.microsoft.com/testdrive/browser/donottrack/

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Non-Discriminative: Access to Locations

‣ Application-level limitations:

‣ Not all locations are the same.

‣ Not all situations are the same.

‣ Not all information destinations are the same.

‣ Default is overpowering

Control is ToughWhat happens when we ask the user to control complex sharing preferences?

How can we balance usability and privacy?

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Crowdsourcing Privacy Preferences

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Aggregator

Preference

Application

Collecting preferences and their underlying context

ModelerBuilding a model for the preference according to a context

Personalizer Personalizing the model for a specific, given user

Using the preference model in a specific application

Preference

Preference

Preference

Preference

Preference

From: Eran Toch, Crowdsourcing Privacy Management in Context-Aware Applications, Personal and Ubiquitous Computing, 2013.

Our User Study‣ 30 Users, 2 weeks.

‣ Smart-Spaces: Tracking locations and activities.

‣ Participants were surveyed three times a day.

‣ Asked about their willingness to share their location on a Likert scale.

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Place Discrimination

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Some places are shared by almost everybody

Some places are

considered private

21 3 4 5

Lesslikely to share More likely to share

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Accuracy of Decision Strategies

Defaults are Enormously Important

‣ People have a tendency to stick to the defaults:

‣ Organ donation choices

‣ Access control policies

‣ Browser selection

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Generating Defaults

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Oded Maimon, Ron Hirschprung, Eran Toch. Evaluating Bi-Directional Data Agent Applicability and Design in Cloud Com- puting Environment, In proceedings of the 17th Industrial Engineering Conference, 2012.

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Testing the Defaults

‣ Privacy is a long-term relationship.

‣ Applications need to provide an ongoing access to privacy data and controls.

‣ Meaningful recourse (helping with problems) is crucial for the user’s security and trust.

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Access and Recourse

Personal Data Centers

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Privacy through Time

Digital information is hardly erased.With search engines and timelines, it becomes more and more accessible. What are the consequences for user-controllable privacy?

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‣ Between-subject user study (n=298)

‣ Analyzing differences between users, randomly assigned to three conditions:

‣ One month

‣ One year

‣ Two years

‣ More than two years.

‣ Using a custom FB application.

Our Study

Eran Toch and Oshrat Rave-Ayalon. Understanding the Temporal Aspects of Sharing Preferences in Online Social Networks, Submitted to SOUPS 2013

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Willingness to Share Over Time

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Implications for Design

A default expiration time of 1.5 years

‣ The best solution for privacy is trying not to know anything about the user.

‣ In most interesting applications, its not possible.

‣ However, analyzing the minimal data requirements for an application is always an interesting idea.

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Data Minimizatio

n

Anonymity Levels

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More recognition Less recognition

Pri

vacy

Gu

ara

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Identified

Pseudo-anonymo

us

Anonymous

Pseudo-anonymous Profiles

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Managing Identity

‣ Don’t ask users to identify.

‣ If users need personalized service, rely on pseudo-anonymous identification.

‣ Use k-Anonymity, l-diversity, p-closeness and differential privacy to release user information.

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Architectural Choices

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Client

Client

Client

Server The privacy bottleneck

Client

Client

Client

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Eran TochDepartment of Industrial Engineering Tel Aviv University, Israel

http://toch.tau.ac.il/

erant@post.tau.ac.il