1 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Real-world trust policies Vinicius Almendra Daniel Schwabe Dept. of Informatics, PUC-Rio ISWC’05

2 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Agenda Problem Statement What Does Trust Mean? The Trust Model Building Real-world Trust Policies An Example Future Work Conclusions

3 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Problem Statement Scenario: collection of semantic web data Through exchange: P2P networks, semantic social desktops Through web navigation: Piggy Bank-like approaches Problem: is this information trustful?

4 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 What Does Trust Mean? Using a real-world model of trust: “trust is reliance on received information” (Gerck, 1998) To trust someone or something => To rely on it to achieve some goal Reliance on a banking Website to move money Reliance on a car or plane while doing a trip Reliance on a statistical software Reliance implies an action (actual or future) – boolean value

5 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Reliance Reliance is NOT Blind Static Irrevocable Reliance depends on Reasoning Circumstances Beliefs Freedom

6 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 What Does Trust Mean? Reliance is useful because It gives a mental frame to think about trustfulness It links trust with action, while keeping them apart Why real-world trust? The model is being built in order to support an easy mapping from daily trust decisions to a computable representation

7 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 The Trust Model To trust is to virtually rely Trust is subjective: it depends on who trusts, the trusting agent Object of trust: facts Statements about reality Facts can be just known (asserted) and can also be trusted. Trust decision: happens when the trusting agent decides that an asserted fact can be trusted

8 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 The Trust Model Trust decision must be reasonable: there must be a justification for accepting that a fact is trustful Justification is based on beliefs, which are grounded on trusted facts A trust policy is a set of rules that the trust agent uses to deduce the trustfulness of a fact. It is associated with a goal Trust policies should be built incrementally

9 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Trust policies Answer the question: “is this fact trustful?” Reasoning behind a trust decision can be expressed using classic logic Trust policy = predicate over a fact asserting its trustfulness Fact = (s,p,o,c) – subject, predicate, object and context Reasoning about trusted facts May use the domain theory of the agent Example: “I trust that a person A is a friend of a person B when A is my friend and B is known to be a person”

10 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Trust Policies If the facts below were trusted: (‘Me’, ‘friend’, ‘John’, ‘My context’) (‘Erick’, ‘type’, ‘Person’, ‘My context’) This fact would be trusted (‘John’, ‘friend’, ‘Erick’, ‘My context’) But not these one (‘Mary’, ‘friend’, ‘John’, ‘Mary’s context’) (‘John’, ‘brother’, ‘Erick’, ‘Robert’s context’)

11 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Trust Policies Trust axiom Given a fact (s,p,o,c) Given a trust policy P

12 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Trust Policies Trust Policies can be combined through aggregation (union of trustful facts) or specialization (intersection of trusted facts)

13 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Scenario: a person looking for trustful news- related information We start with three policies: Self-trust: trust everything contained in “my” context Context info: trust everything stated about a context Good News: trust news that come from friends

14 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Policies described as Prolog clauses: trustedFact(S,P,O,C) :- assertedFact(S,P,O,C), goodNewsRelatedInfo(S,P,O,C). goodNewsRelatedInfo(S,P,O,C) :-selfTrust(S,P,O,C). goodNewsRelatedInfo(C,_,_,C). goodNewsRelatedInfo(S,P,O,C) :- goodNews(S,P,O,C). goodNews(_,rdf:type, 'news:News',C) :- trustedFact(C, dc:creator, Friend, _), trustedFact(myself, foaf:knows, Friend, my_context).

15 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts I foaf:knows John (my context) Self-trust Context info Good news

16 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts I foaf:knows John (my context) Self-trust Context info Good news

17 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Self-trust Context info Good news I foaf:knows John (my context)

18 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts _mary dc:creator Mary ( _mary) Self-trust Context info Good news I foaf:knows John (my context)

19 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts _mary dc:creator Mary ( _mary) Self-trust Context info Good news I foaf:knows John (my context)

20 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Self-trust Context info Good news I foaf:knows John (my context) _mary dc:creator Mary ( _mary)

21 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Football_news rdf:type news:News ( _mary) Self-trust Context info Good news I foaf:knows John (my context) _mary dc:creator Mary ( _mary)

22 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Football_news rdf:type news:News ( _mary) Football_news dc:description ‘Brazil World Cup champ’ ( _mary)’ Self-trust Context info Good news I foaf:knows John (my context) _mary dc:creator Mary ( _mary)

23 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Football_news rdf:type news:News ( _mary) Football_news dc:description ‘Brazil World Cup champ’ ( _mary)’ I foaf:knows mary (my context) Self-trust Context info Good news I foaf:knows John (my context) _mary dc:creator Mary ( _mary)

24 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Football_news rdf:type news:News ( _mary) Football_news dc:description ‘Brazil World Cup champ’ ( _mary)’ I foaf:knows mary (my context) Self-trust Context info Good news I foaf:knows John (my context) _mary dc:creator Mary ( _mary)

25 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Football_news rdf:type news:News ( _mary) Football_news dc:description ‘Brazil World Cup champ’ ( _mary)’ Self-trust Context info Good news I foaf:knows John (my context) _mary dc:creator Mary ( _mary) I foaf:knows mary (my context)

26 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Football_news dc:description ‘Brazil World Cup champ’ ( _mary)’ Self-trust Context info Good news I foaf:knows John (my context) _mary dc:creator Mary ( _mary) I foaf:knows mary (my context) Football_news rdf:type news:News ( _mary)

27 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 An Example – Trust in News Info Asserted factsTrust policiesTrusted facts Self-trust Context info Good news I foaf:knows John (my context) _mary dc:creator Mary ( _mary) I foaf:knows mary (my context) Football_news rdf:type news:News ( _mary) Football_news dc:description ‘Brazil World Cup champ’ ( _mary)’

28 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Implementation A first implementation was done using named graphs We moved to logic programs (XSB Prolog) to better represent trust policies Next step: link these logic programs with a RDF triple store.

29 © 2005, Daniel Schwabe. Vinicius Almendra – SWPW – ISWC05 Conclusions and Future Work Simple approach promising Ongoing work Handling negation – could be pushed to the underlying KB Adding support to inference – to take advantage of the domain knowledge Linking with RDF triple stores Providing a method to build trust policies that keeps “real-world” property Build to help users specify policies Apply to realistic case study