fine-grained trust assertions for privacy management in the social semantic web

Copyright 2011 Digital Enterprise Research Institute. All rights reserved.

Digital Enterprise Research Institute www.deri.ie

Enabling Networked Knowledge

Fine-Grained Trust Assertions for Privacy Management in the

Social Semantic Web

Owen Sacco, John G. Breslin & Stefan Decker

[email protected] TrustCom 2013 – Melbourne Australia Tuesday 16th July 2013



Introduction

Current Social Networks provide generic privacy settings for sharing information do not take user’s trust into account



Introduction

In reality, we only share parts of our information to whom we trust



Research Contribution

In this work we focus on:

Using various methods to automatically

assert fine-grained subjective trust

values for different Social Factors to grant

or restrict access to personal information



Use Case

1. Alex sends a request to view John’s personal information

2. Alex is granted access to the information which his trust value (asserted by John) satisfies a trust threshold (assigned by John)

Example: Provide John’s phone number to Alex if he has a trust level of 0.83

Social Web Platforms...

1

2

Alex

John



Defining Trust

In our work trust is defined as:

“a person’s subjective belief that another person will act

responsibly and will not misuse the information”



Social Factors

Trust judgments are influenced by Social Factors:

Past interactions with a person Opinions of a person’s actions Other people’s opinions Rumours Psychological factors impacted over time Life events and so forth

These can be hard to compute since the information required is limited and unavailable in Social Networks



Social Factors

However, we have identified several factors that trust can be asserted from the information available in Social Networks:

Identity Profile Similarity Relationship type Reputation in a Web of Trust Interactions



Trust Assertion Framework

Social Web Platforms...

Alex

JohnSocial Semantic Web Platform

Trust Manager

1

2

1

2

3 54

6



Social Semantic Web



Trust Model

Trust values are represented in the range of [-1,1]

1 represents absolute trust 0 represents either uncertainty or unknown -1 represents absolute distrust Positive values less than 1 represents trust but with an

element of uncertainty This also applies to negative values



Trust Assertions Model

Identity-based Trust Relies on authentication The WebID protocol is used as a Single Sign-On Service

for Semantic Web applications– WebID provides users to authenticate using FOAF and

X.509 certificates over SSL

The subjective trust value is assigned to the requester after s/he authenticates using WebID

1 if successful, -1 if unsuccessful and 0 if aborted

Definition 1: Identity-based Trust

Certificate(Cert,R) ∧ Profile(RP,R) ∧ Verify(Cert,RP) ∧ AssertedBy(R,U) ⇒ AssignTrust(IDT,R)




Profile Similarity-based Trust Asserting trust based on the similarities between the user

profile and the requester Basic information attributes are not taken into consideration Attributes such as work place information, interests, connected

peers and other profile attributes are compared

Profile similarity-based trust calculation:

– τ denotes profile similarity subjective trust value – m denotes the matched distinct profile attributes between the

user’s profile and the requester’s profile – a denotes the user’s distinct profile attributes




Definition 2: Profile Similarity-based Trust

∀UA(Profile(RP,R) ∧ Profile(UP,U) ∧ Contain(RA,RP)∧Contain(UA,UP) ∧ Match(RA,UA) ∧

AssertedBy(R,U)) ⇒ AssignTrust(PST,R)

where PST ∈ {-1,1}




Relationship-based Trust The Social Semantic Web provides the user to enter a

value of how much s/he trusts that particular relationship type

Definition 3: Relationship-based Trust

∀URT(Profile(UP,U) ∧ Contain(URT,UP) ∧

Relationship(R,URT) ∧ AssertedBy(R,U)) ⇒ AssignTrust(RLP,R)

where RLP ∈ {-1,1}




Reputation-based Trust Consists of a trust value of a user within a Social graph based

on all trust values given by other users Reputation-based trust value is the weighted average value of

all trust values given to a user– The user’s trust values assigned within a network– The weights denotes the reputation value of the person that

assigned the trust value

Reputation-based trust calculation:

– τ denotes reputation trust – w denotes the reputation of the user assigning a subjective trust

value to the requester– v denotes the requester’s subjective trust value assigned by a user




Definition 4: Reputation-based Trust

SocialGraph(SG,U) ∧ Contain(R,SG) ∧ Measure(RV,SG) ∧ Reputaion(RV,R) ∧ AssertedBy(R,U) ⇒ AssignTrust(RPT,R)

where RPT∈ {-1,1}




Interactions-based Trust Consists of users sharing microblog posts, comments,

photos, videos, links and other content with their peers

Interactions-based trust calculation:

– τ denotes interactions trust value– r denotes the number of interactions between the

requester and the user – u denotes the number of all the user’s interactions in the

Social Web platform




Definition 5: Interactions-based Trust

∀UI(Profile(UP,U) ∧ Contain(UI,UP) ∧ Interaction(R,UI) ∧ AssertedBy(R,U)) ⇒ AssignTrust(INTT,R)

where INTT ∈ {-1,1}




Aggregating Subjective Trust Values To assign a fine-grained user’s subjective trust value to

a requester An average of all the subjective trust values of a

requester from each social factor assigned by the user

Aggregate subjective trust calculation:

– τ denotes the aggregated subjective trust value– s a subjective trust value asserted based on a social factor



Trust Assertion Ontology (TAO)

http://vocab.deri.ie/tao



Information Confidentiality

http://vocab.deri.ie/ppo



Implementing Trust Assertions



Results



Future Work

To show how this model is useful for other scenarios (for example for Recommender Systems)

To calculate automatically Relationship-based Trust values

To take into account the trust values of Certificate Authorities when calculating Identity-based Trust

To compare our model with other state-of-the-art models



Thanks!

Email: [email protected]

fine-grained trust assertions for privacy management in the social semantic web

Education

work trust

absolute trust

trust level

trust threshold

web of trust interactions

networked knowledge

users profile

social graph