The Index Poisoning Attack in P2P File Sharing Systems

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The Index Poisoning Attack in P2P File Sharing Systems Keith W. Ross Polytechnic University

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The Index Poisoning Attack in P2P File Sharing Systems. Keith W. Ross Polytechnic University. Jian Liang. Naoum Naoumov. Joint work with:. Internet Traffic. CF: CacheLogic. File Distribution Systems: 2005. Attacks on P2P: Decoying. Two types: File corruption: pollution - PowerPoint PPT Presentation

Transcript of The Index Poisoning Attack in P2P File Sharing Systems

Page 1: The Index Poisoning Attack in   P2P File Sharing Systems

The Index Poisoning Attack in

P2P File Sharing Systems

Keith W. RossPolytechnic University

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• Jian Liang • Naoum Naoumov

Joint work with:

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Internet Traffic

CF: CacheLogic

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File Distribution Systems: 2005

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Attacks on P2P: Decoying

Two types:• File corruption: pollution• Index poisoningInvestigated in two networks:• FastTrack/Kazaa

– Unstructured P2P network

• Overnet– Structured (DHT) P2P network– Part of eDonkey

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File Pollution

pollution company

polluted content

original content

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File Pollution

pollution company

pollution server

pollution server

pollution server

pollution server

file sharingnetwork

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File Pollution

Unsuspecting usersspread pollution !

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File Pollution

Unsuspecting usersspread pollution !

Yuck

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Index Poisoning

index title location bigparty 123.12.7.98smallfun 23.123.78.6heyhey 234.8.89.20

file sharingnetwork

123.12.7.98

23.123.78.6

234.8.89.20

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Index Poisoning

index title location bigparty 123.12.7.98smallfun 23.123.78.6heyhey 234.8.89.20123.12.7.98

23.123.78.6

234.8.89.20

index title location bigparty 123.12.7.98smallfun 23.123.78.6heyhey 234.8.89.20bighit 111.22.22.22

111.22.22.22

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Overnet: DHT

• (version_id, location) stored in nodes with ids close to version_id

• (hash_title, version_id) stored in nodes with ids close to hash_title

• First search hash_title, get version_id and metada

• Then search version_id, get location

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Overnet0001

0011

0100

0101

10001010

1100

1111

PublishQuery

Download

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FastTrack Overlay

Each SN maintains a local index

ON =ordinary node

SN = super node

SN

ON

ONON

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FastTrack Query

ON =ordinary node

SN = super node

SN

ON

ONON

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FastTrack Download

ON =ordinary node

SN = super node

SN

ON

ONON

HTTP requestfor hash value

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FastTrack Download

ON =ordinary node

SN = super node

SN

ON

ONON

P2P file transfer

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Attacks: How Effective?

• For a given title, what fraction of the “copies” are– Clean ?– Poisoned?– Polluted?

• Brute-force approach:– attempt download all versions– For those versions that download, listen/watch

each one

• How do we determine pollution levels without downloading?

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Titles, versions, hashes & copies

• The title is the title of song/movie/software

• A given title can have thousands of versions

• Each version has its own hash

• Each version can have thousands of copies

• A title can also have non-existent versions, each identified by a hash

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Definition of Pollution and Poisoning Levels

• (t, t+ Δ): investigation interval

• V: set of all versions of title T

• V1, V2, V3: sets of poisoned, polluted, clean versions

• Cv: number of advertised copies of version v

Vvv

Vvv

i C

C

L i

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How to Estimate?

• Need Cv, vєV

• Need V1, V2, V3

– Don’t want to download and listen to files!

Solution:

• Harvest Cv, vєV, and copy locations– Overnet: Insert node, receive publish msg’s– FastTrack: Crawl

• Heuristic for V1, V2, V3

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Copies at Users

FastTrack Overnet

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Heuristic

• Identify heavy and light publishers

• Hh = set of hashes from heavy publishers

• Hl = set of hashes from light publishers

polluted versions

cleanversionspoisoned

versions

Hh

Hl

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Heuristic: More

Evaluation #Download # Success #Accuracy # False

Polluted 8,450 8,400 99.4% 0.6% (positive)

Poisoned 33,186 1,156 96.5% 3.5% (negative)

Heuristic is accurate & does not involve any downloading!

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FastTrack Versions

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FastTrack Copies

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Overnet Copies

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Blacklisting

• Assign reputations to /n subnets– Bad reputation to subnets with large

number of advertised copies of any title

• Obtain reputations locally; share with distributed algorithm

• Locally blacklist /n subnets with bad reputations

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Blacklisting: More

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The Inverse Attack• Attacks on P2P systems:

• But can also exploit P2P sytems for DDoS attacks against innocent host:

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Summary&

Thank You!