Roman Schlegel City University of Hong Kong Kehuan Zhang Xiaoyong Zhou Mehool Intwala Apu Kapadia XiaoFeng Wang Indiana University Bloomington NDSS SYMPOSIUM.

R o m a n S c h l e g e lC i t y U n i v e r s i t y o f H o n g K o n g

K e h u a n Z h a n g

X i a o y o n g Z h o u

M e h o o l I n t w a l a

A p u K a p a d i a

X i a o F e n g Wa n gI n d i a n a U n i v e r s i t y B l o o m i n g t o n

N D S S S Y M P O S I U M 2 0 11報告人：張逸文

Soundcomber ：A Stealthy and Context-Aware Sound Trojan for

Smartphones

2

Outline

IntroductionOverviewContext-Aware Information CollectionStealthy Data TransmissionDefense ArchitectureEvaluationDiscussionConclusion

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Introduction（ 1/2）

Full-fledged computing platformsThe plague of data-stealing malware

Sensory malware, ex： video camera, microphoneSecurity protections

Java virtual machines on Android Anti-virus Control installing un-trusted software

Tow new observations Context of phone conversation is predictable and fingerprinted Built-in covert channel

http://nakedsecurity.sophos.com/2010/07/29/android-malware-steals-info-million-phone-owners/

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Introduction（ 2/2）

Main goal： Extract a small amount of high-value private data from phone

conversations and transmit it to a malicious partyMajor contributions：

Targeted, context-aware information discovery from sound recordings

Stealthy data transmission Implementation and evaluation Defensive architecture

5

Outline


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Overview（ 1/2）

Assumptions work under limited privileges

Architectural overview

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Overview（ 2/2）

Video Demo.

4392 2588 8888 8888

8

Outline


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Context-Aware Information Collection（ 1/7）

monitor the phone state identify, record, analysis, extract

1. Audio recording2. Audio processing3. Targeted data extraction

using profiles

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1. Audio recording When to record

Whenever the user initiates a phone call Recording in the background Determining the number called

intercept outgoing phone calls / read contact data the first segment compare with keywords in database relevant, non-overlapping keywords minimize necessary permissions

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2. Audio processing decode file speech/tone recognition speech/tone extraction

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a) tone recognition DTMF（ dual-tone multi-frequency）

signaling channel to inform mobile phone network of the pressed key aural feedback leaks to side-channel Goertzel’s algorithm

http://macao.communications.museum/chi/exhibition/secondfloor/moreinfo/2_6_1_DTMF.html

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b. Speech recognition Google service： speech recognition functionality PocketSphinx Segmentation --- contain speech

sound

silence

n

jxn

thrk

thrk

gthr

n

k

kf

g

n

jsk

f

s

Recordin

0

Recordin

2

0

1

1

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3. Targeted data extraction using profiles focus on IVRs （ Interactive Voice Response system）

Phone menus based on predetermined profiles

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general profiles Speech signatures Sequence detection Speech characteristics

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Outline


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Stealthy Data Transmission

Processing centrally isn’t idealNo local processing on 1 minute recording → 94KBCredit card number → 16 bytesLegitimate, existing application with network accessA paired Trojan application with network access and

communication through covert channel

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Leveraging third-party applications

Permission mechanism only restricts individual application Ex： using browser open URL http : // target ? number=N

drawback： more noticeable due to “foreground” Ads to cover

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Covert channels with paired Trojans（ 1/4）

paired Trojans： Soundminer, DelivererInstallation of paired Trojan applications

Pop-up ad. Packaged app.

Covert channels on the smartphone Vibration settings Volume settings Screen File locks

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Vibration settings any application can change the vibration settings communication channel： every time the setting is changed, the system

sends a notification to interested applications saving and restoring original settings at opportune times no permissions needed not leave any traces

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Volume settings not automatically broadcasted set and check the volume alternatively 3 bits per iteration Sending at times

Reading at times miss a window

Screen invisible visible channel covert channel： screen settings prevent the screen from actually turning on permission WAKE_LOCK

11000

,......,0,ti

msktkt is

2iis ttkt

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File locks exchange information through competing for a file lock signaling files, S1,……,Sm

one data file S1~Sm/2 for Soundminer , Sm/2+1~Sm for Deliverer

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Outline


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Defense Architecture

add a context-sensitive reference monitor to control the AudioFinger service

block all applications from accessing the audio data when a sensitive call is in progress

Reference Service RIL（ radio interface layer） enter/leave a sensitive state

Controller Embedded in the AudioFinger service Exclusive Mode / Non-Exclusive Mode

http://www.cnblogs.com/innost/archive/2011/01/15/1936425.html

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Outline


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Evaluation（ 1/2）

Experiment settings Environment Service hotline detection Tone recognition Speech recognition --- getrusage() Profile-based data discovery --- extracted high-value information Cover channel study --- bandwidth in bits per second Reference monitor

http://blog.csdn.net/rojay520/archive/2007/01/22/1489964.aspx

http://blog.csdn.net/rojay520/archive/2007/01/22/1489964.aspx

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Evaluation（ 2/2）

Experiment results Effectiveness

Service hotline detection Tone/speech recognition Detection by anti-virus applications

Performance

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Outline


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Discussion

Improvements on attackDefenses

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Conclusion

Soundminer, innocuous permissionsDefense on sensor data stealingHighlighted the threat of stealthy sensory malware

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Thanks ~

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Goertzel’s algorithm

http://ptolemy.eecs.berkeley.edu/papers/96/dtmf_ict/www/node3.html

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Performance

Roman Schlegel City University of Hong Kong Kehuan Zhang Xiaoyong Zhou Mehool Intwala Apu Kapadia XiaoFeng Wang Indiana University Bloomington NDSS SYMPOSIUM.

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