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This discussion outlines the use of social relationships to guide interactions online, focusing on transitive trust relationships and privacy concerns. Models, constructions, and implementations are discussed to address these issues efficiently and securely. Applications of proximity checking in various scenarios are also explored.
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Efficient Private Techniques for Verifying Social Proximity Michael J. Freedman and Antonio Nicolosi Discussion by: A. ZiadHatahet
Outline • Introduction • The Problem • Motivation • Model • Constructions • Discussion
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 • Compare list of friends/contacts and find intersection • Privacy issues
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 • 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
Model • Social link should express consent of both parties • Forward trust • , • Backward authorization • ,
Constructions • Hash-based construction • Privacy in the face of collusions
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 • 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 • 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?
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?
Discussion • How would a malicious user exploit the system? • Viruses • Sybil attacks • Are the consequences worse? • Anything else?
Proximity Checking • Consider , and • For , S encrypts attestation • where is a secure symmetric cipher • and • S also includes • tab
Proximity Checking • S creates list of tabbed encrypted attestations (one for each incoming social relationship), and sends to R along with request
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 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