Privacy-Preserving Profile Matching for Proximity-Based Mobile Social Networking

  title={Privacy-Preserving Profile Matching for Proximity-Based Mobile Social Networking},
  author={Rui Zhang and Jinxue Zhang and Yanchao Zhang and Jinyuan Sun and Guanhua Yan},
  journal={IEEE Journal on Selected Areas in Communications},
Proximity-based mobile social networking (PMSN) refers to the social interaction among physically proximate mobile users. The first step toward effective PMSN is for mobile users to choose whom to interact with. Profile matching refers to two users comparing their personal profiles and is promising for user selection in PMSN. It, however, conflicts with users' growing privacy concerns about disclosing their personal profiles to complete strangers. This paper tackles this open challenge by… 

Figures and Tables from this paper

Privacy-preserving multi-hop profile-matching protocol for proximity mobile social networks

Overview on Privacy-Preserving Profile-Matching Mechanisms in Mobile Social Networks in Proximity (MSNP)

  • Yufeng WangJ. Xu
  • Computer Science
    2014 Ninth Asia Joint Conference on Information Security
  • 2014
Two primary approaches to solving the privacy-preserving profile-based friend matching problem, including private set intersection (PSI) and vector dot product to measures the social proximity, are categorized and compared.

NMHP: A Privacy Preserving Profile Matching Protocol in Multi-hop Proximity Mobile Social Networks

Security analysis shows that the proposed protocol can realize privacy-preserving friend discovery with higher efficiency and utilize the confusion matrix transformation and the idea of multi-hop, which means to make profile matching within several hops instead one.

A Differentially Private Matching Scheme for Pairing Similar Users of Proximity Based Social Networking applications

This paper matches users in a proximity-based social network setting adapted from a framework of differential privacy, which eliminates the need for third-party matching schemes, allows for accurate matching, and ensures malicious users will be unable to infer information from matching results.

Privacy Preserving Profile Matching in Mobile Social Networks: A Comprehensive Survey

This paper reviews the work done in the domain of privacy and security issues of profile matching and provides a comprehensive analysis on it.

Survey of Privacy Preserving Friend Matching Protocol for Pre-match in Social Networks

This survey is about matching protocols that enable two users to perform profile matching without disclosing any information about their profile to find out the bugs or threats.

User self-controllable profile matching for privacy-preserving mobile social networks

A user self-controllable profile matching protocol in privacy-preserving mobile social networks is proposed that can protect the privacy of both users' profile item names and profile item values during the matching process.

A Cloud Aided Privacy-Preserving Profile Matching Scheme in Mobile Social Networks

  • Qiong ChengChong-zhi Gao
  • Computer Science
    22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC)
  • 2017
This paper designs a cloud aided privacy-preserving profile matching scheme to efficiently compute social proximity between two users to discover potential friends without disclosing the personal privacy to others.

Privacy Preserving and Fully Anonymous Protocols for Profile Matching in Mobile Social Networks

iCPM is generalized into an implicit Predicate-based Profile Matching protocol (iPPM) which allows complex comparison criteria spanning multiple attributes.

A Trustless Broker Based Protocol to Discover Friends in Proximity-Based Mobile Social Networks

The proposed protocol does not require trustworthy broker and hence no valuable information is given to broker that can cause a privacy threat, and paillier encryption has been used in the protocol.



Fine-grained private matching for proximity-based mobile social networking

This paper designs a suite of novel fine-grained private matching protocols for proximity-based mobile social networking that allow finer differentiation between PMSN users and can support a wide range of matching metrics at different privacy levels.

FindU: Privacy-preserving personal profile matching in mobile social networks

This paper proposes FindU, the first privacy-preserving personal profile matching schemes for mobile social networks, and proposes novel protocols that realize two of the user privacy levels, which can also be personalized by the users.

Secure friend discovery in mobile social networks

A novel solution for secure proximity estimation is developed, which allows users to identify potential friends by computing social proximity in a privacy-preserving manner and provides both privacy and verifiability, which are frequently at odds in secure multiparty computation.

VENETA: Serverless Friend-of-Friend Detection in Mobile Social Networking

VENETA is presented, a mobile social networking platform which, among other features, implements the novel friend of friend detection algorithm, and adequately addresses the arising privacy issues.

A New Privacy-Enhanced Matchmaking Protocol

An adversary model is defined, which captures the key security properties of privacy-enhanced matchmaking, and it is shown that a simple, practical protocol derived by a two-step transformation of a password-based authenticated key exchange counters adversary attacks in a provable manner (in the standard model of cryptographic security).

E-SmallTalker: A Distributed Mobile System for Social Networking in Physical Proximity

E-SmallTalker is a distributed mobile communications system that facilitates social networking in physical proximity that automatically discovers and suggests topics such as common interests for more significant conversations and proposes a novel iterative Bloom filter protocol that encodes topics to fit in SDP attributes and achieves a low false positive rate.

Secure handshake with symptoms-matching: the essential to the success of mhealthcare social network

A secure same-symptom-based handshake (SSH) scheme is proposed, and the provable security technique is applied to demonstrate its security in the random oracle model.

JR-SND: Jamming-Resilient Secure Neighbor Discovery in Mobile Ad Hoc Networks

JR-SND is proposed, a jamming-resilient secure neighbor discovery scheme for MANETs based on Direct Sequence Spread Spectrum and random spread-code pre-distribution that enables neighboring nodes to securely discover each other with overwhelming probability despite the presence of omnipresent jammers.

Privacy-preserving collaborative filtering using randomized perturbation techniques

This work proposes a randomized perturbation (RP) technique to protect users' privacy while still producing accurate recommendations in collaborative filtering.

Efficient Cryptographic Primitives for Private Data Mining

  • Mark ShaneckYongdae Kim
  • Computer Science, Mathematics
    2010 43rd Hawaii International Conference on System Sciences
  • 2010
This work creates a novel protocol for privately computing dot product, a foundational primitive for many private data mining activities, and investigates trade-offs that can be made in the trust model, thus reducing the amount of trust needed in the third party.