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On Protecting Private Information in Social Networks: A Proposal. Bo Luo 1 and Dongwon Lee 2 1 The University of Kansas, [email protected] 2 The Pennsylvania State University, [email protected] Motivation. Online social networks

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On protecting private information in social networks a proposal l.jpg

On Protecting Private Information in Social Networks: A Proposal

Bo Luo1 and Dongwon Lee2

1 The University of Kansas, [email protected]

2 The Pennsylvania State University, [email protected]

Motivation l.jpg
Motivation Proposal

  • Online social networks

    • Getting very popular (e.g. Facebook: 68M unique visitors, 1.2B visits)

    • Various types of communities

      • General (e.g. Facebook; MySpace)

      • Business/professional (e.g. LinkedIn)

      • Alumni

      • Leisure

      • Healthcare (e.g. SoberCircle; PatientsLikeMe)

  • People socialize with friends

  • But also adversaries!

Motivation3 l.jpg
Motivation Proposal

  • Privacy vulnerabilities in online social networks

    • Huge amount of personal information available over various types of social network sites.

    • Users are not fully aware of the risks.

    • Adversaries use various techniques to collect such information.

      • E.g. information retrieval and search engine

  • News stories

    • Facebook Stalkers [Dubow, USA Today, 2007]

    • Gadgets and add-ons read user profiles [Irvin, USA Today, 2008]

    • How Not to Lose Face on Facebook, for Professors. [Young, Chronicle, 2009]

    • .

Privacy vulnerabilities l.jpg
Privacy vulnerabilities Proposal

  • Threat 1: out-of-context information disclosure

    • Users present information to a “context” (e.g. targeted readers)

    • Implicit assumption

      • Information stays in the context

      • This is wrong!

    • Out-of-context information disclosure

      • Wrong configuration

      • Mal-functioning code

      • Users’ misunderstanding

  • Examples

    • Adversaries could simply register for forums to access many information.

    • Messages in a “closed” email-based community is archived and accessible to everyone.

    • Gadgets and add-ons read user profiles

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Privacy vulnerabilities Proposal

  • Threat 2: In-network information aggregation

    • User share information in social networks

    • Implicit assumption: “a small piece of personal information is not a big deal”

    • Adversaries collect all the pieces of information associated with a user.

    • Adversaries aggregate all the information pieces.

    • Significant amount of privacy!

    • In-network information aggregation attack.

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Privacy vulnerabilities Proposal

  • Threat 3: cross-network information aggregation

    • User participates in multiple networks

    • Different levels of privacy concerns.

    • Adversaries use evidences to link profiles from different SN sites

      • Attribute

      • Neighborhood

      • Similar posts

      • Propagation

    • Adversaries collects all the private information across multiple SN sites

    • Cross-network information aggregation

Goals and solutions at a glance l.jpg
Goals and solutions at a glance Proposal

  • Goal: prevent users from unwanted information disclosure, especially from the three threats.

  • Users should be able to socialize.

    • We cannot prevent users from sharing information

  • Honest-but-curious observer

    • Honest: no phishing, no spam, no hacking

    • Curious: very aggressive in seeking information

      • Registers for social networks

      • Uses search engines

      • Manipulates information

  • Our goal:

    • Protect users from honest-but-curious observers

Design goals l.jpg
Design goals Proposal

  • Enable users to describe a privacy plan——How they allow their private information items to be disclosed

    • Solution: privacy models

  • Alert users when they share information over social networks

    • Solution: passive monitor

  • Monitor private information over various social networks to make sure that they are not violated

    • Solution: active monitor

Online social networks l.jpg
Online social networks Proposal

  • We define two properties to describe online social networks

    • Openness level

      • How information in a social network could be accessed

      • E.g. OL=public– everyone can access;

      • E.g. OL=registration-required– all registered users can access, but not search engines.

    • Access equivalency group

      • Social networks with identical openness level belongs to a group.

Private information model l.jpg
Private information model Proposal

  • We define two private information models

  • Multi-level model

    • Private information items are managed in hierarchically organized categories

    • Information flow from lower level (less private) to higher level (more private)

      • E.g. when user trusts SN with level 3, s/he also trusts SN with levels 1 and 2

    • Simple model

    • Easy for users to understand

    • Less descriptive

Private information model11 l.jpg
Private information model Proposal

  • Discretionary model—— a set-based model

    • Private information items are organized into sets

    • Private information items in one set could be released together

    • Private information item may belong to multiple sets

  • Private information disclosure model

    • Formally describes:

      • out-of-context information disclosure

      • information aggregation attacks

        under discretionary model.

    • Details: please refer to the paper

Privacy sandbox l.jpg
Privacy sandbox Proposal

  • Picks a privacy model

  • Allows users to describe their privacy plan in the model, i.e. how they want to arrange private information items

    • E.g. define privacy information sets under discretionary model

    • Define how sets could be released to social networks with different openness level.

  • Keeps privacy plans

Passive monitor l.jpg
Passive monitor Proposal

  • Passive monitor

    • is triggered when users send information to social networks

    • Alerts users

      • who can access the submitted information

      • Openness level

      • Access equivalency group

    • Checks against the privacy plan

    • Keeps a local log of private information disclosure

      • For future use

Remote component and active monitor l.jpg
Remote Component and Active monitor Proposal

  • Remote component

    • Actively collects personal information from various social networks

    • Simulates in-network and cross-network information aggregation

    • Stores information in a data repository

  • Active monitor

    • Compares users’ privacy plans with

      • Local log

      • Remote data repository

      • Search engine results

    • Checks for discrepancy

      • Warns user about unwanted information disclosure

Conclusion l.jpg
Conclusion Proposal

  • In this paper, we

    • present privacy vulnerabilities over social networks, especially information aggregation attacks

    • model social networks and private information disclosure from access control perspective

    • describe information aggregation attacks in the model

    • propose our initial design of a privacy monitor

  • This is our preliminary proposal

  • Further analysis and implementation is on-going

  • Thanks a lot!