14. Research
Reliability
&
Validity
Pilot
tesIng
Random
order
of
answers
ValidaIon
quesIons
Post
sampling
Summaries
generalizable
to
populaIons
DifferenIal
analysis
with
significant
results
!
14
15. 408
Valid
Responses
(out
of
595)
Developers
Users
North
America
85
44
Europe
116
65
Asia/Pacific
61
30
15
16. Outline
of
the
Talk
ImplicaSons
Study
Design
Results
MoSvaSon
2
1
3
4
16
17. Privacy
Concerns
Data
AggregaSon
AggregaIon
of
user
data
over
long
period
of
Ime
Data
DistorSon
MisrepresentaIon
of
the
data
or
user
intent
Data
Sharing
Collected
data
given
to
third
parIes
e.g.
for
adverIsing
Data
Breaches
Malicious
users
get
access
to
sensiIve
data
17
19. Selected
QualitaSve
Feedback
AuthoriSes
and
intelligent
services
“Anyway
there
is
prism”
Unusable
and
non-‐
transparent
policies
Lack
of
control
APIs,
correctness
&
viruses
“Privacy
concerns
are
transmiZed
through
APIs”
19
20. Reducing
Privacy
Concerns
• Privacy
Policy
and
license
agreements
• Privacy
Laws
e.g.
HIPAA
or
EU
Privacy
DirecIve
• AnonymizaSon
removing
personal
idenIfiers
• Technical
Details
e.g.
encrypIon
algorithm
• Details
on
Usage
how
different
data
are
used
20
22. Selected
QualitaSve
Feedback
Period
and
amount
of
data
Easy,
fine-‐grained
control
over
data
“It
should
be
possible
to
disagree
with
certain
terms”
CerSficaSon
from
independent
trusted
organizaSons
“A
privacy
police
to
check
how
data
is
handled”“privacy
audits”
Transparency
and
open
source
22
23. CriScality
of
Different
Types
of
Data
Metadata
Interaction
Preferences
Location
Personal Data
Content
200 100 0 100
Metadata
Interaction
Preferences
Location
Personal Data
Content
200 100 0 100200 100 0 100
Very Critical Critical Neutral Somewhat Uncritical Uncritical 23
24. Give
up
Privacy?
• Monetary
discounts
(e.g.,
10%
discount
on
the
next
purchase)
• “Intelligent”
or
added
funcSonality
(such
as
the
Amazon
recommendaIons)
• Fewer
adverSsements
24
25. Would
you
Give
up
Privacy
for…?
#responses
Ads
Money
Functionality
200 100 0 100 #responses200 100 0 100 #responses
# responses
Ads
Money
Functionality
200 100 0 100 # responses200 100 0 100 # responses
No Uncertain Yes
FuncIonality
Money
Ads
25
26. PercepSons
of
Developers
vs.
Users
Developers
Users
Concerns
about
data
distorSon
and
aggregaSon
Low
High
MiSgaSng
privacy
concerns
AnonymizaIon
&
usage
details
AnonymizaIon,
usage
details,
policies
&
laws
equally
effecIve
26
27. PercepSons
Based
on
Geography
North
America
Europe
MiSgaSng
privacy
concerns
Usage
details,
laws,
and
policies
equally
effecIve
Usage
details
Data
criScality
Low
High
Give
up
privacy
for
funcSonality?
More
likely
Less
likely
27
28. Outline
of
the
Talk
ImplicaSons
Study
Design
Results
MoSvaSon
2
1
3
4
28
29. Biggest
Privacy
Concerns
29
"Kathy
Simon
-‐
originally
posted
to
Flickr
as
Viola
and
Mina
share
food"
31. Towards
a
Privacy
Framework
• AnonymizaIon
• Data
usage
details
• Fine-‐grained
control
over
data
• Metadata
and
interacIon
data
first
• Time
and
space
limited
storage
• Privacy
“licenses”
31
34. Us
and
Them:
A
Study
of
Privacy
Requirements
Across
North
America,
Asia,
and
Europe
Swapneel
Sheth,
Gail
Kaiser,
Walid
Maalej
Columbia
University,
University
of
Hamburg
@swapneel
@maalejw
bit.ly/privacy-‐requirements
34
