SybilLimit: A Near-Optimal Social Network Defense Against Sybil Attacks

1
SybilLimit A Near-Optimal Social Network Defense
Against Sybil Attacks

• Haifeng Yu National University of Singapore
• Phillip B. Gibbons Intel Research Pittsburgh
• Michael Kaminsky Intel Research Pittsburgh
• Feng Xiao National University of Singapore

2
Background Sybil Attack
honest

• Sybil attack Single user pretends many
  fake/sybil identities
• Already observed in real-world p2p systems
• Sybil identities can become a large fraction of
  all identities
• Out-vote honest users in collaborative tasks

malicious
3
Background Defending Against Sybil Attack

• Using trusted central authority to tie identities
  to human beings not always desirable
• Much harder without a trusted central authority
  Douceur02
• Resource challenges not sufficient
• IP address-based approach not sufficient
• Widely considered as real challenging
• Over 40 papers acknowledging the problem of sybil
  attack, without having a distributed solution

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SybilGuard / SybilLimit Basic Insight
Leveraging Social Networks
SybilGuard SIGCOMM06 / SybilLimit
Oakland08 The first to leverage social
networks for thwarting sybil attacks with
provable guarantees.

• Nodes identities
• Undirected edges strong mutual trust
• E.g., colleagues, relatives in real-world
• Not online friends !

5
Attack Model

• n honest users One identity/node each
• Malicious users Multiple identities each (sybil
  nodes)

honest nodes
attack edges
malicious users
Observation Adversary cannot create extra edges
between honest nodes and sybil nodes
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SybilGuard/SybilLimit Basic Insight

• Dis-proportionally small cut disconnecting a
  large number of identities

But cannot search brute-force
attack edges
honest nodes
sybil nodes
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SybilGuard / SybilLimit End Guarantees

• Completely decentralized
• Enables any given verifier node to decide whether
  to accept any given suspect node
• Accept Provide service to / receive service from
• Ideally Accept and only accept honest nodes
  unfortunately not possible
• SybilGuard / SybilLimit provably
• Bound of accepted sybil nodes (w.h.p.)
• Accept all honest nodes except a small ? fraction
  (w.h.p.)

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Example Application Scenarios
If of sybil nodes accepted Then applications can do
lt n/2 byzantine consensus
lt n majority voting
lt n/c for some constant c secure DHT Awerbuch06, Castro02, Fiat05

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SybilLimit Contribution 1 Pushing the Limit
sybil nodes accepted (smaller is better) per
attack edge
total number of attack edges SybilGuard SIGCOMM06 SybilLimit Oakland08


between
unbounded
and
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Outline

• Motivation, basic insight, and end guarantees
• SybilLimit Contribution 1 Pushing the Limit
• The near-optimal SybilLimit design
• SybilLimit Contribution 2 Validation on
  Real-World Social Networks

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Identity Registration in SybilLimit

• Each node (honest or sybil) has a locally
  generated public/private key pair
• Identity V accepts S V accepts Ss public
  key KS
• We do not assume/need PKI
• In SybilLimit, every suspect S registers KS on
  some other nodes

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SybilLimit Strawman Design Step 1
K registered keys of sybil nodes

• Ensure that sybil nodes (collectively) register
  only on limited number of honest nodes
• Still provide enough registration opportunities
  for honest nodes

K registered keys of honest nodes
K
K
K
K
K
K
sybil region
honest region
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SybilLimit Strawman Design Step 2
K registered keys of sybil nodes

• Accept S only if KS is register on sufficiently
  many honest nodes
• Without knowing where the honest region is !
• Circular design? We can break this circle

K registered keys of honest nodes
K
K
K
K
K
K
K
K
K
K
K
K
K
K
K
K
sybil region
honest region
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Three Interrelated Key Techniques

• Technique 1 Use the tails of random routes for
  registration
• Will achieve Step 1
• Random routes are from SybilGuard
• Novelty The use of tails
• Novelty The use of multiple independent
  instances of shorter random routes

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Three Interrelated Key Techniques

• Technique 2 Use intersection condition and
  balance condition to verify suspects
• Will break the circular design and achieve Step 2
• SybilGuard also has intersection condition
• Novelty Intersection on edges
• Novelty SybilGuard has no balance condition
• Technique 3 Use benchmarking technique to
  estimate unknown parameters
• Breaks another seemingly circular design
• Novelty SybilGuard has no such technique

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Three Interrelated Key Techniques

• Technique 1 Use the tails of random routes for
  registration
• Will achieve Step 1
• Random routes are from SybilGuard
• Novelty The use of tails
• Novelty The use of multiple independent
  instances of shorter random routes

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Random Route Convergence
f
a
e
b
d
a ? d
d ? e
c
randomized routing table
b ? a
e ? d
c ? b
f ? f
d ? c
Using routing table gives Convergence Property
Routes merge if crossing the same edge
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Registering Public Keys with Tails

• Every node initiates a secure random route of
  length w from itself
• See paper for discussion on w
• See paper for how to make it secure

edge C?D is the tail of As random route
w 3
A
D records KA under name C?D
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Tails of Sybil Suspects

• Imagine that every sybil suspect initiates a
  random route from itself

sybil nodes
honest nodes
total 1 tainted tail
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Counting The Number of Tainted Tails
attack edge
honest nodes
sybil nodes

• Claim There are at most w tainted tails per
  attack edge
• Convergence At most w tainted tails per attack
  edge
• Regardless of whether sybil nodes follow the
  protocol

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Back to the Strawman Design Step 1

• of K s ? g?w
• Independent of sybil nodes
• of K s ? n g?w
• From backtrace-ability property of random
  routes
• See paper

K registered keys of sybil nodes K registered
keys of honest nodes
K
K
K
K
honest region
K
K
K
Step 1 achieved !
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Outline

• SybilLimit Contribution 1 Pushing the Limit
• Independent instances, intersection condition,
  balance condition, benchmarking technique
• Avoids multiple seemingly circular designs
  (hardest part)
• Also see paper for
• Performance overheads
• Near-optimality
• SybilLimit Contribution 2 Validation on
  Real-World Social Networks

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Validation on Real-World Social Networks

• SybilGuard / SybilLimit assumption Honest nodes
  are not behind disproportionally small cuts
• Rigorously Social networks (without sybil nodes)
  have small mixing time
• Mixing time affects sybil nodes accepted and
  honest nodes accepted
• Synthetic social networks proof in SIGCOMM06
• Real-world social networks?
• Social communities, social groups, .

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Simulation Setup
Crawled online social networks used in experiments
nodes edges
Friendster 0.9M 7.8M
Livejournal 0.9M 8.7M
DBLP 0.1M 0.6M

• We experiment with
• Different number and placement of attack edges
• Different graph sizes -- full size to 100-node
  sub-graphs
• Sybil attackers use the optimal strategy

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Brief Summary of Simulation Results

• In all cases we experimented with
• Fraction of honest nodes accepted
• 95
• sybil nodes accepted
• 10 per attack edge for Friendster and
  LiveJournal
• 15 per attack edge for DBLP

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Conclusions

• Sybil attack
• Widely considered as a real and challenging
  problem
• SybilLimit Fully decentralized defense protocol
  based on social networks
• Provable near-optimal guarantees
• Experimental validation on real-world social
  networks
• Future work Implement SybilLimit with real apps