LinkDroid: Reducing Unregulated Aggregation of …LinkDroid: Reducing Unregulated Aggregation of...
Transcript of LinkDroid: Reducing Unregulated Aggregation of …LinkDroid: Reducing Unregulated Aggregation of...
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LinkDroid: Reducing Unregulated Aggregation of App-Usage Behaviors
Huan Feng, Kassem Fawaz, Kang G. Shin
Real-Time Computing Laboratory, University of Michigan
24th USENIX Security SymposiumAugust 14th, 2015 • Washington DC
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An Emerging Threat
Unregulated Aggregation of App-Usage Behaviors
An Emerging Threat
Dynamic Linkability Graph(DLG)
A Novel Perspective
DLG in the real-world
Real-world Evidence
LinkDroid: Runtime Monitoring& Mediation
Proposed Solution
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Political Interests
Travel History Financial Assets
Dating & Relationship
An Emerging Threat
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Political Interests
Travel History Financial Assets
Dating & Relationship
An Emerging Threat
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Political Interests
Travel History Financial Assets
Dating & Relationship
An Emerging Threat
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Analytics & Advertising Agency
Acquisitions of IT Companies
Surveillance Agency
An Emerging Threat
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Analytics & Advertising Agency
Acquisitions of IT Companies
Surveillance Agency
A curious adversary is able to aggregate usage behaviors of the same user across multiple apps without his knowledge or consent.
The threat of Unregulated Aggregation of App-Usage Behaviors
Realistic, financially-motivated, more promising in the future.
An Emerging Threat
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A Novel Perspective
Dynamic Linkability Graph(DLG)
A Novel Perspective
DLG in the real-world
Real-world Evidence
LinkDroid: Runtime Monitoring& Mediation
Proposed Solution
Unregulated Aggregation of App-Usage Behaviors
An Emerging Threat
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Advertising Agency IT Company?
Challenges
? ?
A Novel Perspective
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A Novel Perspective
Challenges
New paradigms (πBox, MoRePriv) ---> modify app & ecosystem
???
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A Novel Perspective
isolated
Mobile OS
A Different Perspective
• Characterize & monitor the linkability across mobile apps• Two apps are linkable if can associate behaviors of the same user
• Pre-requisites of conducting aggregation
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A Novel Perspective
isolated
Mobile OS
OS-Level Information
Inter-Process Communications
Explicitly via Binder, or implicitly via shared storage (e.g. SD Card).
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A Novel Perspective
isolated
Mobile OS
13 Sources of Linkability
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
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1. Client-side information is enough2. Quantify the privacy threat (though upper bound)
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
Linkable: Two apps are linkable if there exists a path between them.
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
Linkable: Two apps are linkable if there exists a path between them.
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
Linkable: Two apps are linkable if there exists a path between them.
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
Linking Ratio (LR): # of apps an app is linkable to, divided by all installed apps
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
Linking Ratio (LR): # of apps an app is linkable to, divided by all installed apps
LRA= 6 / 8
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
Distance: The # of connecting nodes between two linkable apps
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
Distance: The # of connecting nodes between two linkable apps
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability Graph
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
Linking Effort (LE): average distance between an app and all the apps it’s linkable to
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability GraphLinking Effort (LE): average distance between an app and all the apps it’s linkable to
A
0
0
0
1
12
I
H
Android ID
Intent IPCPhone Number
MAC Address
LEA= 0 + 2 + 2 / 6
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability GraphGlobal Linking Ratio (GLR) & Global Linking Effort (GLE)
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability GraphGLR: Probability of two random apps being linkable (quantity)
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
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A Novel Perspective
Mobile OS
DLG: Dynamic Linkability GraphGLE: Average distance between two linkable apps (quality)
A
B
C
D
F
EG
I
H
Android ID
Intent IPCPhone Number
MAC Address
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Real-world Evidence
Unregulated Aggregation of App-Usage Behaviors
An Emerging Threat
Dynamic Linkability Graph(DLG)
A Novel Perspective
DLG in the real-world
Real-world Evidence
LinkDroid: Runtime Monitoring& Mediation
Proposed Solution
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Real-world Evidence
DLG: A Mobile Extension
• Alternative approaches• User-level Interception (Aurasium)
• Dynamic OS Instrumentation (Xposed Framework)
• Monitor various access to OS-level Info & IPC Channels• System Services (Wifi, Telephony, etc)
• Content Provider
• Intent Firewall
• FUSE Daemon
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Real-world Evidence
The Alarming Findings
• DLG of 13 users during 47 days using 215 unique apps• GLR = 0.81 (two random apps are linkable -> 81%)
• GLE = 0.2 (control 0.2 additional apps, on average)
• 86% of the apps a user installed are linkable to Facebook, namely his real identity
• Linkability is contributed by various factors (sources)• Device ID leads, with others following closely behind
• Using only contextual information, 40% of apps is linkable to Facebook
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Real-world Evidence
The Alarming Findings
• DLG of 13 users during 47 days using 215 unique apps• GLR = 0.81 (two random apps are linkable -> 81%)
• GLE = 0.2 (control 0.2 additional apps, on average)
• 86% of the apps a user installed are linkable to Facebook, namely his real identity
• Linkability is contributed by various factors (sources)• Device ID leads, with others following closely behind
• Using only contextual information, 40% of apps is linkable to Facebook
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Linkability contributed by different sources are proportional to the % of apps accessing each source, except for quasi-identifiers.
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Functional Analysis
• OS-level Information• Device ID no need for the actual identifiers
• Personal ID abuse user accounts & phone #
• Contextual ID exploit Location & nearby AP
• IPC Communications• Apps report their installation using Intents (WeChat)
• Apps bind to service & exchange user IDs (Facebook, AdMob)
• Apps read identifiers written by other apps (Qingting Radio)
• Subject to personal preference and application context
Real-world Evidence
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Proposed Solution
Unregulated Aggregation of App-Usage Behaviors
An Emerging Threat
Dynamic Linkability Graph(DLG)
A Novel Perspective
DLG in the real-world
Real-world Evidence
LinkDroid: Runtime Monitoring& Mediation
Proposed Solution
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LinkDroid
• Designed with practicality in mind• No modification of apps, no additional trusted parties
• Works purely on the client-side
• A new dimension to privacy protection on mobile OS• How app behaviors implicitly affect linkability
• Opt-out & reduce unnecessary links
• Features provided by LinkDroid• Install-time Obfuscation
• DLG-powered Runtime Monitoring
• Unlinkable Mode
Proposed Solution
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LinkDroid
Install-time Obfuscation
Device ID (Android ID, IMEI, etc)
Proposed Solution
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RuntimeMonitoring
LinkDroid
Phone #
Intent
Proposed Solution
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RuntimeMonitoring
LinkDroid
Phone #
Intent
Behavioral Description of the Scenario
Descriptive Risk Indicator
Quantitative Risk Indicator
Opt-out Options
Proposed Solution
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LinkDroid
Phone #
IntentUnlinkableMode
Proposed Solution
A new instance installed on a new device
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Design of LinkDroid
Proposed Solution
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Proposed Solution
• Evaluated on the same set of 13 participants as in the measurement• Replay traces collected in the measurement with LinkDroid features
• GLR (two random apps being linkable): 81% to 21%
• GLE (additional apps required to link two apps): 0.22 to 0.68• Under most scenarios, at least one additional app is required
• Apps directly linkable to Facebook dropped from 86% to 18%
Evaluation
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DLG of a representative user before and after applying LinkDroid. (Red circle is the Facebook app)
(a) before (b) after
Proposed Solution
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Proposed Solution
Takeaway
Leaked (shared) information should NOT be linkable unless REALLY necessary
Linkability: a useful but MISSING notion in the mobile ecosystem
Anonymous (unlinkable) in-app behaviors should be a BASIC right
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Questions?
Huan Feng
LinkDroid: Reducing Unregulated Aggregation of App-Usage Behaviors