efficient private techniques for verifying social proximity
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Efficient Private Techniques for Verifying Social Proximity. Michael J. Freedman and Antonio Nicolosi Discussion by: A. Ziad Hatahet. Outline. Introduction The Problem Motivation Model Constructions Discussion. Introduction. Transitive trust relationships

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efficient private techniques for verifying social proximity

Efficient Private Techniques for Verifying Social Proximity

Michael J. Freedman and Antonio Nicolosi

Discussion by: A. ZiadHatahet

outline
Outline
  • Introduction
  • The Problem
  • Motivation
  • Model
  • Constructions
  • Discussion
introduction
Introduction
  • Transitive trust relationships
  • Goal: to leverage social relationships to guide interactions with others users in online systems that use social networks.
  • Email or IM contexts
    • Black/white-listing
the problem
The Problem
  • Compare list of friends/contacts and find intersection
  • Privacy issues
motivation
Motivation
  • Content-based spam filters
    • False positives
  • Whitelists
    • Forge From: addresses
    • Does not accept email from previously unknown sources
    • Populating requires manual effort
  • RE:
    • Automatically expands set of senders who to accept email from by examining user’s social network
    • Does not prevent parties from “lying” about information they present (friends they give out)
model
Model
  • Social network can be modeled as a directed graph where a presence of an arc (or ) indicates existence of social relationship
  • Find bridgingfriends and
  • Privacy concerns
model1
Model
  • Social link should express consent of both parties
  • Forward trust
    • ,
  • Backward authorization
    • ,
constructions
Constructions
  • Hash-based construction
  • Privacy in the face of collusions
hash based implementation
Hash-Based Implementation
  • Each user R has a signing/verification key pair SKR/VKR, and a secret seed for cryptographic pseudo-random hash function F
  • For each social link , user R creates an attestation for user X and sends it along with . R receives from X.
  • Each arc is associated with a (pseudo-)random key (a-value)
privacy in the face of collusions
Privacy in the Face of Collusions
  • Backward authorization implemented in hash-based scheme is transferable
  • Hash-based scheme, R gives out the same secret to all X s.t.
  • Solution: different shared secret key to each X
  • Proximity check protocol uses same overall structure as that of hash-based scheme
discussion
Discussion
  • Where else can this be applied?
    • P2P file sharing
    • Bluetooth
    • Phone services/VoIP
  • Does the model make sense?
    • It is assumed that system has proximity check mechanism
    • Can be implemented at a higher level?
  • How to transfer attestations?
discussion1
Discussion
  • How to revoke attestations?
    • Time limit
  • Is collusion a privacy concern?
    • Would share their resources anyway!
  • What are the effects of multi-hop proximity?
    • Is it practical/safe?
discussion2
Discussion
  • How would a malicious user exploit the system?
    • Viruses
    • Sybil attacks
    • Are the consequences worse?
  • Anything else?
proximity checking
Proximity Checking
  • Consider , and
  • For , S encrypts attestation
    • where is a secure symmetric cipher
    • and
  • S also includes
    • tab
proximity checking1
Proximity Checking
  • S creates list of tabbed encrypted attestations (one for each incoming social relationship), and sends to R along with request
proximity checking2
Proximity Checking
  • User R processes list by looking at tab components
  • Looks for relationships of the form
  • Since R holds
    • can compute
    • Generates own set of tabs
    • Compares with received from S
proximity checking3
Proximity Checking
  • Match between tabs guarantees same seed was used by both R and S
  • Bridging friend T revealed
  • R computes key and decrypts encrypted attestation, recovering
  • Concludes and
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