Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Adaptiveness and Social-Compliancein Trust Management –
a Multi-Agent Based Approach
Reda Yaich
ISCODInstitut Henri FayolEcole des Mines
Saint-Etienne
29 October 2013
1
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Open and Decentralised Virtual Communities
A
D
C
G
E
B
F
H
f
Frank
George
EliseCarl
Alice
Dave
Bob
Helen
A group of people with a common purpose whose interactions aremediated and supported by computer platforms” [Preece, 2004]
2
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust in Virtual Communities
In virtual communities, decisions made by members are risky anduncertainI Who can access my resources?I Who can join my community?
Does security help?I Resources and actors should be known !
I How much credit can I assign to the partner?I Who is the best partner I can interact with?
TrustTrust enables people to make decisions in complex environmentsbased on positive expectations [Luhmann, 1990]
3
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust in Virtual Communities
In virtual communities, decisions made by members are risky anduncertainI Who can access my resources?I Who can join my community?
Does security help?I Resources and actors should be known !
I How much credit can I assign to the partner?I Who is the best partner I can interact with?
TrustTrust enables people to make decisions in complex environmentsbased on positive expectations [Luhmann, 1990]
3
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust in Virtual Communities
In virtual communities, decisions made by members are risky anduncertainI Who can access my resources?I Who can join my community?
Does security help?I Resources and actors should be known !
I How much credit can I assign to the partner?I Who is the best partner I can interact with?
TrustTrust enables people to make decisions in complex environmentsbased on positive expectations [Luhmann, 1990]
3
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust in Virtual Communities
In virtual communities, decisions made by members are risky anduncertainI Who can access my resources?I Who can join my community?
Does security help?I Resources and actors should be known !
I How much credit can I assign to the partner?I Who is the best partner I can interact with?
TrustTrust enables people to make decisions in complex environmentsbased on positive expectations [Luhmann, 1990]
3
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Objectives
Design a system that assists members of open and decentralisedvirtual communities in their trust decisions
Challenging PropertiesI Openness: people can join and leave communities at willI Dynamics: ever-evolving contextI Social-Compliance: self-interests vs. collective objectivesI Decentralization: no central authority
4
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Objectives
Design a system that assists members of open and decentralisedvirtual communities in their trust decisions
Challenging PropertiesI Openness: people can join and leave communities at willI Dynamics: ever-evolving contextI Social-Compliance: self-interests vs. collective objectivesI Decentralization: no central authority
4
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
1 Introduction
2 Research ScopeTrust Management LandscapeObjectives
3 Trust Management System (TMS)
4 Adaptive TMS (A-TMS)
5 Adaptive and Socially-Compliant TMS (ASC-TMS)
6 Evaluation
7 Conclusion
5
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust in Computer Science
ACLPolicyMaker
IBM TE
STM
Rei
PGP(WoT)
ReGret FIRE LIAR
ForTrust
PROTUNE
Attributes
Trust Management Negotiation
CTM
Reputation Reliability
Deontic
hybrid
Roles
SocialTrust
Social Trust
TrustBuilder
Ponder
X.509(PKI)
SocialRelations
Trust Model
MAS
XACML1.0
XACML3.0
XACML2.0
ComputationalTrust
RT
2000 20121970 2005 20081990
ATNAC
Soft
Trus
t App
roac
hes
Har
d Tr
ust A
ppro
ache
s
6
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Hard vs Soft Trust Approaches
How the challenging properties have been addressed?
Hard Trust Soft TrustOpenness Attributes ExperienceDynamics Policies Context-Awareness
Social-Compliance Integration Social Control/NormsDecentralization Delegation Multi-Agent
7
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Research Objectives
Assist virtual communitymembers in their trustdecisions taking intoaccount:I Openness
I DynamicsI Social-ComplianceI Decentralization
8
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Research Objectives
Assist virtual communitymembers in their trustdecisions taking intoaccount:I OpennessI Dynamics
I Social-ComplianceI Decentralization
Trust Factors Trust Policy
8
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Research Objectives
Assist virtual communitymembers in their trustdecisions taking intoaccount:I OpennessI DynamicsI Social-Compliance
I Decentralization
Trust Factors Trust Policy
AdaptivenessIndividual Policy Adaptation to the
Environment
Individual Policy Adaptation to the
Partner
8
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Research Objectives
Assist virtual communitymembers in their trustdecisions taking intoaccount:I OpennessI DynamicsI Social-ComplianceI Decentralization Trust Factors Trust Policy
AdaptivenessIndividual Policy Adaptation to the
Environment
Individual Policy Adaptation to the
Partner
Social-Compliance
Individual Policy Adaptation to the Collective
Collective Policy Adaptation to the Individual
8
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Research Objectives
Assist virtual communitymembers in their trustdecisions taking intoaccount:I OpennessI DynamicsI Social-ComplianceI Decentralization
Multi-Agent Based Trust Management System
Trust Factors Trust Policy
AdaptivenessIndividual Policy Adaptation to the
Environment
Individual Policy Adaptation to the
Partner
Social-Compliance
Individual Policy Adaptation to the Collective
Collective Policy Adaptation to the Individual
8
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
1 Introduction
2 Research Scope
3 Trust ManagementSystem (TMS)
Trust FactorsOntologyFlexible PolicyLanguage
4 Adaptive TMS (A-TMS)
5 Adaptive andSocially-Compliant TMS(ASC-TMS)
6 Evaluation
7 Conclusion
Trust Factors Trust Policy
9
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust Factors Ontology (TFO) ∆f
A hybrid trust management approach
TrustFactor
10
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust Factors Ontology (TFO) ∆f
A hybrid trust management approach
TrustFactor
IndicatorProof
Subsumption
Disjonction
10
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust Factors Ontology (TFO) ∆f
A hybrid trust management approach
TrustFactor
IndicatorProof
Reliability
Selfishness
Experience
Reputation
Subsumption
Disjonction
10
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust Factors Ontology (TFO) ∆f
A hybrid trust management approach
TrustFactor
IndicatorProof
Reliability
Selfishness
Experience
ReputationDegree
Competences
Experience
Membership
Subsumption
Disjonction
10
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust Factors Ontology (TFO) ∆f
A hybrid trust management approach
TrustFactor
IndicatorProof
Reliability
Selfishness
Experience
ReputationDegree
Competences
Experience
Prof.
PhDMaster
Licence
Bachelor
Engineer
Membership
Subsumption
Disjonction
Is A
10
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust Factors Ontology (TFO) ∆f
A hybrid trust management approach
TrustFactor
IndicatorProof
Reliability
Selfishness
Experience
ReputationDegree
Competences
Experience
Prof.
PhDMaster
Licence
Bachelor
Engineer
Membership
Subsumption
Lower
Disjonction
Higher
Is A
10
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Trust Factors Ontology (TFO) ∆f
A hybrid trust management approach
TrustFactor
IndicatorProof
Reliability
Selfishness
Experience
ReputationDegree
Competences
Experience
Prof.
PhDMaster
Licence
Bachelor
Engineer
Membership
Subsumption
Lower
Equivalent
Disjonction
Higher
Is A
10
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Policy Language
A policy is defined by a set of trust criteriaπPattern
Issuer = {〈f1, o1, v1,w1, t1〉, ..., 〈fn, on, vn,wn, tn〉}Where :I fi is the trust factor name (f ∈ ∆f .T )I oi is a comparison operator from (oi ∈ {>, <,≤,≥,,,=})I vi is a threshold value (vi ∈ ∆f .A )I wi is a weight value (wi ∈ Z)I ti ∈ {’m’, ’o’} specifies if the criterion is mandatory or not
Bob’s policy for the pattern 〈access, notes〉
π〈access,notes〉bob = {〈identity,≥,marginal, 2,m〉,
〈age, >, 18, 2,m〉, 〈age, <, 30, 2,m〉,
〈reputation,≥, 60%, 2, o〉,
〈recommendation,≤, 2, 1, o〉}11
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Policy Evaluation
The evaluation E(πxa , ψ
b) of:The policy πx
a = {〈f1, op1, v1,w1, t1〉, . . . , 〈fn, opn, vn,wn, tn〉}With respect to the profile ψb = 〈q, b , {〈f1, v′1〉, . . . , 〈fm, v
′m〉}〉
E(πxa , ψ
b) =
∑n
i=1,j=1 E(〈fi ,opi ,vi ,wi ,ti〉,〈fj ,v′j 〉)∑ni=1 wi
0 if a mandatory criterion is not satisfied
where:
E(〈fi , opi , vi ,wi , ti〉, 〈fj , v′j 〉) =
wi if fi = fj and fi opi fj0, otherwise
(1)
12
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Illustration of Policy Evaluation
Policy Evaluation
tc(identity,≥, marginal, 2, m)
tc(reputation,≥, 70, 2, o)
tc(recommendation,≥, 3, 1, o)
credential(age, alice, 25)
declaration(reputation, alice, 50)
declaration(recommendation, alice, 0)
tc(age, <, 30, 2, m)
tc(age, >, 18, 2, m)
Policy of the controller
Profile of the requester
credential(identity, alice, complete)
2 + 2 + 2 + 0 + 0
9= 0.66
13
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Illustration of Policy Evaluation
Policy Evaluation
tc(identity,≥, marginal, 2, m)
tc(reputation,≥, 70, 2, o)
tc(recommendation,≥, 3, 1, o)
credential(age, alice, 25)
declaration(reputation, alice, 75)
declaration(recommendation, alice, 0)
tc(age, <, 30, 2, m)
tc(age, >, 18, 2, m)
Policy of the controller
Profile of the requester
credential(identity, alice, unknown)
0
13
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
1 Introduction
2 Research Scope
3 Trust ManagementSystem (TMS)
4 Adaptive TMS (A-TMS)Individual toEnvironmentIndividual ToIndividual
5 Adaptive andSocially-Compliant TMS(ASC-TMS)
6 Evaluation
7 Conclusion
Trust Factors Trust Policy
AdaptivenessIndividual Policy Adaptation to the
Environment
Individual Policy Adaptation to the
Partner
14
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Policies Obsolescence
A
D
C
G
E
B
F
H
I
f
Frank
George
EliseCarl
Alice
Dave
Bob
Helen
?
Resources - Availability - Values- sensitivity
Trust Factors - Availability- Pertinence
Interaction outcome
Risks - Credentials falsification - Id usurpation - Reputation collusion
Policies specification context , current context15
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Adaptation Meta-Policies
I Adaptive Trust Negotiation and Access Control[Ryutov et al., 2005]
I Extension of the policy language with Adaptationmeta-policies.
I When policies should be adaptedI How they can be adapted
Meta-policiesEvent : Condition ← Actions
Actions include (but not limited to) adaptation operators
I AddCriterion(π, tci)
I DelCriterion(π, fi)I UpdateCriterion(π, fi)
I RelaxCriterion(π, fi)I RestrictCriterion(π, fi)I LowerCriterion(π, fi)I HigherCriterion(π, fi)
16
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Adaptation Meta-Policies
I Adaptive Trust Negotiation and Access Control[Ryutov et al., 2005]
I Extension of the policy language with Adaptationmeta-policies.
I When policies should be adaptedI How they can be adapted
Meta-policiesEvent : Condition ← Actions
Actions include (but not limited to) adaptation operators
I AddCriterion(π, tci)
I DelCriterion(π, fi)I UpdateCriterion(π, fi)
I RelaxCriterion(π, fi)I RestrictCriterion(π, fi)I LowerCriterion(π, fi)I HigherCriterion(π, fi)
16
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Adaptation Meta-Policies
I Adaptive Trust Negotiation and Access Control[Ryutov et al., 2005]
I Extension of the policy language with Adaptationmeta-policies.
I When policies should be adaptedI How they can be adapted
Meta-policiesEvent : Condition ← Actions
Actions include (but not limited to) adaptation operators
I AddCriterion(π, tci)
I DelCriterion(π, fi)I UpdateCriterion(π, fi)
I RelaxCriterion(π, fi)I RestrictCriterion(π, fi)I LowerCriterion(π, fi)I HigherCriterion(π, fi)
16
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Illustration of adaptation to environment
Adaptation to resource value
Instantiate(π〈_,file〉Bob ,R) :R .valuet > R .valuet−1∨
R .sensitivity t > R .sensitivity t−1 ←
RestrictCriterion(π〈_,file〉Bob , reputation),
RestrictCriterion(π〈_,file〉Bob , recommendation)
Initial Policy
π〈read,file〉bob ={〈identity,≥,marginal, 2,m〉,
〈age, >, 18, 2,m〉, 〈age, <, 30, 2, o〉,
〈reputation,≥, 50%, 3, o〉, 〈recommendation, >, 2, 1, o〉}
17
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Illustration of adaptation to environment
Adaptation to resource value
Instantiate(π〈_,file〉Bob ,R) :R .valuet > R .valuet−1∨
R .sensitivity t > R .sensitivity t−1 ←
RestrictCriterion(π〈_,file〉Bob , reputation),
RestrictCriterion(π〈_,file〉Bob , recommendation)
Adapted Policy
π〈read,file〉bob ={〈identity,≥,marginal, 2,m〉,
〈age, >, 18, 2,m〉, 〈age, <, 30, 2, o〉,
〈reputation,≥, 60%, 3, o〉, 〈recommendation, >, 3, 1, o〉}
17
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Adaptation of the Individual to the Partner
Multi-Agent Based Trust Management System
Trust Factors Trust Policy
AdaptivenessIndividual Policy Adaptation to the
Environment
Individual Policy Adaptation to the
Partner
Social-Compliance
Individual Policy Adaptation to the Collective
Collective Policy Adaptation to the Individual
18
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Automated Trust Negotiation
Trust Builder [Yu et al., 2003, Lee et al., 2009], IBM TE[Herzberg et al., 2000], Trust−X [Bertino et al., 2003], RT[Li et al., 2002]
I Evaluation =⇒CredentialsDisclosure
I Credentials =⇒contain sensitiveinformation
I Trust Deadlock !
subject S requests action A on resource R
Evidence for property X ?
Evidence for property Y ?
Evidence for property Y
Evidence for property X
Authorization for S to perform A on R
Controller
Requester
19
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
The Adaptive Trust Negotiation
I NegotiationProtocol
I NegotiationStrategy
I Utility Function
0 1 2 3 4 5
7
6
b: REQUESTa: START-
NEGOTIATIONb: ACCEP-
NEGOTIATION a: QUERY-IF
b: PROPOSE
a: ACCEPT/REJECT -PROPOSAL
b: ACCEPT/REJECT-PROPOSAL
b: CONFIRM/DISCONFIRM
a: PROPOSE
a: CONFIRM / DISCONFIRM
b: QUERY-IF
a: QUERY-IF
b: REFUSE-NEGOTIATION
a: END-NEGOTIATION
b: END-NEGOTIATION
b: END-NEGOTIATION
a: END-NEGOTIATION
20
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
The Adaptive Trust Negotiation
I NegotiationProtocol
I NegotiationStrategy
I Utility Function
C2: confirm
C1: dis- confirm
C3: propose
C3.2:accept-proposal
C3.1:refuse-proposal
query-If
C2.1 : end-negotiation
C2.1:Query-If(continue negotiation)
�1,−1�
�0, 0�
�0, 0��3, 2� �3, 3�
Controller
Requester
Controller
Controller
20
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
The Adaptive Trust Negotiation
I NegotiationProtocol
I NegotiationStrategy
I Utility Function
uc = (O�update,r�controller +
�(xi.ν)) − (r.ς + r.ν)
ur = (O�update,r�requester +
�(xi.ς)) −
�(yi.ν)
Controller
Requester
20
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Illustration
Dis-confirm
Propose
Query-If
�0, 0�Reject ProposalAccept
Proposal
Confirm
Propose
RejectProposal
Confirm End-negotiation�−3, 3�
End-negotiationaccept
�2, 0��0, 0� Accept
Proposal
End-negotiationConfirm
�−3, 3�Confirm
�0, 0�
�1, 1�
�0, 2�
r.ν = 2
r.ς = 2
O�update,r�controller = 3
O�update,r�requester = 3
c1.ν = 1
c2.ν = 2
c3.ν = 3
21
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
1 Introduction
2 Research Scope
3 Trust ManagementSystem (TMS)
4 Adaptive TMS (A-TMS)
5 Adaptive andSocially-Compliant TMS(ASC-TMS)
Individual to CollectiveCollective to IndividualMulti-Agent BasedTMS
6 Evaluation
7 Conclusion
Trust Factors Trust Policy
AdaptivenessIndividual Policy Adaptation to the
Environment
Individual Policy Adaptation to the
Partner
Social-Compliance
Individual Policy Adaptation to the Collective
Collective Policy Adaptation to the Individual
22
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Adaptation of Individual Policies to Collective ones
23
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Adaptation of Individual Policies to Collective ones
23
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Adaptation of Individual Policies to Collective ones
23
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Integration Mechanism
Integration
�f1, o1, v1, w1, t1��f2, o2, v2, w2, t2�.........................
�fn, on, vn, wn, tn�
�f1, o1, v1, w1, t1��f2, o2, v2, w2, t2�.........................
�fn, on, vn, wn, tn�
�f1, o1, v1, w1, t1��f2, o2, v2, w2, t2�.........................
�fn, on, vn, wn, tn� Ri = Rj RjRi
RjRi Ri Rj
RjRi
Ri Converge Rj Ri Diverges Rj
Ri Extends Rj Ri Restricts Rj
Ri Suffles Rj / Rj Suffles Ri
XACML [Humenn, 2003, Cover, 2007], Combination[Rao et al., 2009] and Integration [Rao et al., 2011]
24
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Policies Integration Heuristics
I h1: p is at least as restrictive as the most restrictive policyI I’m sure to deny all requests both policies would have denied
I h2: p is at most as restrictive as the least restrictive policyI I’m sure to accept request that both policies would have
acceptedI h3: p is at least as restrictive as the selected policy
I I’m sure to deny all requests me/my community would havedenied
I h4: p is at most as restrictive as the selected policyI I’m sure to accept all requests me/my community would have
accepted
25
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Illustration of Individual Adaptation to the Collective
Integration
(reputation,≥, 70, 2, o)(recommendation,≥, 2, 3, o)
(identity,≥, fair, 3, m)
(identity,≥, marginal, 4, m)
(identity,≥, marginal, 1, o)
(reputation,≥, 75, 4, o)
(recommendation,≥, 2, 3, o)
Collective Policy
Individual Policy
(reputation,≥, 75, 2, o)
26
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
1 Introduction
2 Research Scope
3 Trust ManagementSystem (TMS)
4 Adaptive TMS (A-TMS)
5 Adaptive andSocially-Compliant TMS(ASC-TMS)
Individual to CollectiveCollective to IndividualMulti-Agent BasedTMS
6 Evaluation
7 Conclusion
Trust Factors Trust Policy
AdaptivenessIndividual Policy Adaptation to the
Environment
Individual Policy Adaptation to the
Partner
Social-Compliance
Individual Policy Adaptation to the Collective
Collective Policy Adaptation to the Individual
27
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Building Collective Policies from Individual Ones
28
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Building Collective Policies from Individual Ones
28
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Combination Mechanism
Combination
�f1, o1, v1, w1, t1��f2, o2, v2, w2, t2�.........................
�fn, on, vn, wn, tn�
�f1, o1, v1, w1, t1��f2, o2, v2, w2, t2�.........................
�fn, on, vn, wn, tn�
�f1, o1, v1, w1, t1��f2, o2, v2, w2, t2�.........................
�fn, on, vn, wn, tn�
�f1, o1, v1, w1, t1��f2, o2, v2, w2, t2�.........................
�fn, on, vn, wn, tn�
Combination driven byheuristicsI h1: Selects the most
restrictive criterioneach time
I h2: Selects the leastrestrictive criterioneach time
29
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Policies Combination
1 Check if the collectivepolicy exists
2 Broadcast the call3 Policies are selected4 Policies are exchanged5 Policies are combined6 The collective policy is
generated
30
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Policies Combination
1 Check if the collectivepolicy exists
2 Broadcast the call3 Policies are selected4 Policies are exchanged5 Policies are combined6 The collective policy is
generated
30
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Policies Combination
1 Check if the collectivepolicy exists
2 Broadcast the call
3 Policies are selected4 Policies are exchanged5 Policies are combined6 The collective policy is
generated
30
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Policies Combination
1 Check if the collectivepolicy exists
2 Broadcast the call3 Policies are selected
4 Policies are exchanged5 Policies are combined6 The collective policy is
generated
30
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Policies Combination
1 Check if the collectivepolicy exists
2 Broadcast the call3 Policies are selected4 Policies are exchanged
5 Policies are combined6 The collective policy is
generated
30
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Policies Combination
1 Check if the collectivepolicy exists
2 Broadcast the call3 Policies are selected4 Policies are exchanged5 Policies are combined
6 The collective policy isgenerated
30
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Policies Combination
1 Check if the collectivepolicy exists
2 Broadcast the call3 Policies are selected4 Policies are exchanged5 Policies are combined6 The collective policy is
generated
30
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Policies Combination
1 Check if the collectivepolicy exists
2 Broadcast the call3 Policies are selected4 Policies are exchanged5 Policies are combined6 The collective policy is
generated
30
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Illustration of Individual Policies Combination
Combination
tc(skillfulness,≥, fair, 1, o)
tc(reputation,≥, 70, 2, o)
tc(recommendation,≥, 3, 1, o)
tc(recommendation,≥, 3, 3, o)
tc(reputation,≥, 75, 6, o)
tc(skilfulness,≥, fair, 5, o)
tc(identity,≥, marginal, 8, m)
tc(skilfulness,≥, fair, 2, o)
tc(reputation,≥, 65, 1, o)
tc(recommendation,≥, 2, 2, o)
tc(skilfulness,≥, fair, 2, o)
tc(reputation,≥, 75, 3, o)
tc(identity,≥, fair, 3, 0) tc(identity,≥, marginal, 5, m)
Individual Policy Individual Policy
Individual Policy
I h1: Selects the most restrictive criterion each time
31
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Collective Policies Obsolescence
32
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Collective Policies Evolution
Meta-policiesEvent : Condition ← Actions
Actions include (but not limited to) adaptation operators
I AddCriterion(π, tci)
I DelCriterion(π, fi)I UpdateCriterion(π, fi)
I RelaxCriterion(π, fi)I RestrictCriterion(π, fi)I LowerCriterion(π, fi)I HigherCriterion(π, fi)
33
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Collective Policies Evolution
1 Detection of PolicyObsolescence
2 Call for evolution
3 Vote for adaptation4 Compute votes5 Adapt the policy if
majority
34
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Collective Policies Evolution
1 Detection of PolicyObsolescence
2 Call for evolution3 Vote for adaptation
4 Compute votes5 Adapt the policy if
majority
34
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Collective Policies Evolution
1 Detection of PolicyObsolescence
2 Call for evolution3 Vote for adaptation4 Compute votes
5 Adapt the policy ifmajority
34
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Collective Policies Evolution
1 Detection of PolicyObsolescence
2 Call for evolution3 Vote for adaptation4 Compute votes5 Adapt the policy if
majority
34
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Coordination for Collective Policies Evolution
1 Detection of PolicyObsolescence
2 Call for evolution3 Vote for adaptation4 Compute votes5 Adapt the policy if
majority
34
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Synthesis on Social Compliance
→ Extension of the policy language with Adaptation meta-policies
Meta-policiesEvent : Condition ← Actions
Actions includes context-awareness and social-awarenessoperators
I RelaxCriterion(π, fi)I ...
I Integrate(π1, π2, ih)
I Combine(Π′, c, ch, π′)
→ Definition of coordination protocols
35
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
1 Introduction
2 Research Scope
3 Trust ManagementSystem (TMS)
4 Adaptive TMS (A-TMS)
5 Adaptive andSocially-Compliant TMS(ASC-TMS)
Individual to CollectiveCollective to IndividualMulti-Agent BasedTMS
6 Evaluation
7 Conclusion
Multi-Agent Based Trust Management System
Trust Factors Trust Policy
AdaptivenessIndividual Policy Adaptation to the
Environment
Individual Policy Adaptation to the
Partner
Social-Compliance
Individual Policy Adaptation to the Collective
Collective Policy Adaptation to the Individual
36
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Multi-Agent Based Trust Management System
A
A
AA
AA
Adhesion
Association
Interactions
Community
Role
Collective Policies
A AssistantAgent
Individual Policies
ASC-TMS
Private Resource
Public Resource
T
T
T
T
T
TT
Environment
Agents
Organisation
Interaction
Control
Operation
Negotiation
DecentralizedTrust Management
CoordinationVoting/NegotiationProtocols
Norms& Organisations
37
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Multi-Agent Based Trust Management System
A
A
AA
AA
Adhesion
Association
Interactions
Community
Role
Collective Policies
A AssistantAgent
Individual Policies
ASC-TMS
Private Resource
Public Resource
T
T
T
T
T
TT
Environment
Agents
Organisation
Interaction
Control
Operation
Negotiation
DecentralizedTrust Management
CoordinationVoting/NegotiationProtocols
Norms& Organisations
37
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Multi-Agent Based Trust Management System
A
A
AA
AA
Adhesion
Association
Interactions
Community
Role
Collective Policies
A AssistantAgent
Individual Policies
ASC-TMS
Private Resource
Public Resource
T
T
T
T
T
TT
Environment
Agents
Organisation
Interaction
Control
Operation
Negotiation
DecentralizedTrust Management
CoordinationVoting/NegotiationProtocols
Norms& Organisations
37
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Multi-Agent Based Trust Management System
A
A
AA
AA
Adhesion
Association
Interactions
Community
Role
Collective Policies
A AssistantAgent
Individual Policies
ASC-TMS
Private Resource
Public Resource
T
T
T
T
T
TT
Environment
Agents
Organisation
Interaction
Control
Operation
Negotiation
DecentralizedTrust Management
CoordinationVoting/NegotiationProtocols
Norms& Organisations
37
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Multi-Agent Based Trust Management System
A
A
AA
AA
Adhesion
Association
Interactions
Community
Role
Collective Policies
A AssistantAgent
Individual Policies
ASC-TMS
Private Resource
Public Resource
T
T
T
T
T
TT
Environment
Agents
Organisation
Interaction
Control
Operation
Negotiation
DecentralizedTrust Management
CoordinationVoting/NegotiationProtocols
Norms& Organisations
37
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
1 Introduction
2 Research Scope
3 Trust Management System (TMS)
4 Adaptive TMS (A-TMS)
5 Adaptive and Socially-Compliant TMS (ASC-TMS)
6 EvaluationImplementationRepast SimulationResults
7 Conclusion38
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Implementations
I Demonstrate the applicability of ASC-TMSI Deploy the model on the JaCaMo Platform
[Boissier et al., 2011]I Use of ASC-TMS in Open Innovation Community ApplicationI Extension of the model for mobiles (JaCaAndroid)
I Evaluate ASC-TMSI Implementation on Repast Simulation Platform [Collier, 2003]I Run the model on large scale populationsI Observe the benefit of ASC-TMSI Evaluate the impact of ASC-TMS on communities dynamics
39
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Evaluation Objective
Study the benefit of using social compliance in trust managementwithin virtual communities
I Impact of combination on communities dynamics
I Impact of social-compliance on communities dynamics
I Correlation between social-compliance and communitiesdynamics
I Impact of evolution on communities dynamics
40
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Experimental Settings
Use case: Communities for Open innovation challenges
ChallengesI Objectives: 10 000 resource unitsI Deadline: 1000 stepsI Reward: 1000 $
Rules:I Non Compliant members are ejected from their communityI Empty communities are destroyed (collapse)
Simulation MetricsI Number of communitiesI Population of each community
41
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Experimental Settings
Use case: Communities for Open innovation challenges
ChallengesI Objectives: 10 000 resource unitsI Deadline: 1000 stepsI Reward: 1000 $
Rules:I Non Compliant members are ejected from their communityI Empty communities are destroyed (collapse)
Simulation MetricsI Number of communitiesI Population of each community
41
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Experimental Settings
Use case: Communities for Open innovation challenges
ChallengesI Objectives: 10 000 resource unitsI Deadline: 1000 stepsI Reward: 1000 $
Rules:I Non Compliant members are ejected from their communityI Empty communities are destroyed (collapse)
Simulation MetricsI Number of communitiesI Population of each community
41
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Parameters
AgentsI Policies and Credentials are randomly generatedI Collaborativeness: uniform distribution ([0,1])I Competence: normal distribution ([0,1])I Interaction: probability of 0.8
Different populations in terms of social-complianceI (With/Without) CombinationI With a probability (0/0.5/0.8/1) of IntegrationI (With/Without) Evolution
42
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Impact of combination on communities dynamics
-5
0
5
10
15
20
25
0 2000 4000 6000 8000 10000 12000
Num
ber o
f Com
mun
ities
Simulation Step
No Combination - No Integration - No EvolutionCombination - No Integration - No Evolution
-5
0
5
10
15
20
25
30
35
0 2000 4000 6000 8000 10000 12000
Aver
age
Popu
latio
n Si
ze
Simulation Step
No Combination - No Integration - No EvolutionCombination - No Integration - No Evolution
43
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Impact of integration on communities dynamics
-5
0
5
10
15
20
25
30
35
0 2000 4000 6000 8000 10000 12000
Num
ber o
f Com
mun
ities
Simulation Step
No Combination - No Integration - No EvolutionCombination - No Integration - No EvolutionCombination - 1.0 Integration - No Evolution
-5
0
5
10
15
20
25
30
35
40
0 2000 4000 6000 8000 10000 12000
Aver
age
Popu
latio
n Si
ze
Simulation Step
No Combination - No Integration - No EvolutionCombination - No Integration - No EvolutionCombination - 1.0 Integration - No Evolution
44
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Compliance and Communities Dynamics Correlation
-5
0
5
10
15
20
25
30
35
0 2000 4000 6000 8000 10000 12000
Num
ber o
f Com
mun
ities
Simulation Step
No Combination - No Integration - No EvolutionCombination - No Integration - No EvolutionCombination - 0.5 Integration - No EvolutionCombination - 0.8 Integration - No EvolutionCombination - 1.0 Integration - No Evolution
-5
0
5
10
15
20
25
30
35
40
0 2000 4000 6000 8000 10000 12000
Aver
age
Popu
latio
n Si
ze
Simulation Step
No Combination - No Integration - No EvolutionCombination - No Integration - No EvolutionCombination - 0.5 Integration - No EvolutionCombination - 0.8 Integration - No EvolutionCombination - 1.0 Integration - No Evolution
45
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Impact of Evolution on Communities Dynamics
-5
0
5
10
15
20
25
30
35
40
0 2000 4000 6000 8000 10000 12000
Num
ber o
f Com
mun
ities
Simulation Step
Combination - 1.0 Integration - No EvolutionCombination - 0.8 Integration - EvolutionCombination - 1.0 Integration - Evolution
-5
0
5
10
15
20
25
30
35
40
0 2000 4000 6000 8000 10000 12000
Aver
age
Popu
latio
n Si
ze
Simulation Step
Combination - 1.0 Integration - No EvolutionCombination - 0.8 Integration - EvolutionCombination - 1.0 Integration - Evolution
46
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Results Synthesis
I Without integration (i.e. adaptation of individual trust policiesto collective ones), disappearing of communities is morefrequent
I Social compliance helps communities to work better
I Combination and evolution are important mechanisms to helpagent to maintain communities even if non social compliantmembers exist (up to 20%)
47
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Contributions
I ASC-TMS is a new Hybrid Trust Approach combining Hardand Soft Trust Approaches
I ASC-TMS proposes a rich, expressive and flexible policylanguage addressing both individual and collectivedimensions
I ASC-TMS addresses both individual and collective TrustManagement and Adaptation
I ASC-TMS bridges the gap between Social Science, TrustManagement and Distributed Artificial Intelligence
48
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Future Works
I Extend and enrich the evaluation of ASC-TMS (w.r.t,Populations, Heuristics, Coordination)
I Confront ASC-TMS to Social Science Theories and ExistingTrust Models
I Enrich the expressiveness of the ASC-TMS policy language
I Extend the adaptation mechanisms at the individual andcollective levels with learning capabilities to learn from pastexperiences
I Apply the adaptation mechanism to the evolution of the TrustFactors Ontology
49
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Related Publications
I Yaich, R., Boissier, O., Picard, G., and Jaillon, P. (2013). Adaptiveness and social-compliance in trustmanagement within virtual communities. Web Intelligence and Agent Systems (WIAS), Special Issue: WebIntelligence and Communities (to appear).
I Yaich, R., Boissier, O., Picard, G, and Jaillon, P. (2012). An agent based trust management system for multi-agentbased virtual communities. In Demazeau, Y., Müller, J. P., Rodríguez, J. M. C., and Pérez, J. B., editors,Advances on Practical Applications of Agents and Multiagent Systems, Proc. of the 10th International Conferenceon Practical Applications of Agents and Multi-Agent Systems (PAAMS 12), volume 155 ofAdvances in SoftComputing Series, pages 217-223. Springer.
I Yaich, R., Boissier, O., Jaillon, P., and Picard, G. (2012). An adaptive and socially-compliant trust managementsystem for virtual communities. InThe 27th ACM Symposium On Applied Computing (SAC 2012), pages2022-2028. ACM Press.
I Yaich, R., Boissier, O., Picard, G., and Jaillon, P. (2011). Social-compliance in trust management within virtualcommunities. In European Workshop on Multi-agent Systems (EUMAS’11).
I Yaich, R., Boissier, O., Jaillon, P., and Picard, G. (2011). Social-compliance in trust management within virtualcommunities. In 3rd International Workshop on Web Intelligence and Communities (WI&C’11) at the InternationalConferences on Web Intelligence and Intelligent Agent Technology (WI-IAT 2011), pages 322-325. IEEEComputer Society.
I Yaich, R., Jaillon, P., Boissier, O., and Picard, G. (2011). Gestion de la confiance et intgration des exigencessociales au sein de communautés virtuelles. In 19es Journées francophones des systèmes multi-agents(JFSMA’11), pages 213-222. Cépaduès.
I Yaich, R., Jaillon, P., Picard, G., and Boissier, O. (2010). Toward an adaptive trust policy model for open anddecentralized virtual communities. InWorkshop on Trust and Reputation. Interdisciplines.
50
Introduction Research Scope TMS A-TMS ASC-TMS Evaluation Conclusion
Thank You for Your Attention !
Questions ?
51
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Humenn, P. (2003).
The formal semantics of XACML.
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References III
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Li, N., Mitchell, J. C., and Winsborough, W. H. (2002).
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Luhmann, N. (1990).
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Preece, J. (2004).
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References V
Rao, P., Lin, D., Bertino, E., Li, N., and Lobo, J. (2009).
An algebra for fine-grained integration of xacml policies.
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Rao, P., Lin, D., Bertino, E., Li, N., and Lobo, J. (2011).
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References VI
Ryutov, T., Zhou, L., Neuman, C., Leithead, T., and Seamons, K. E.(2005).
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In Proceedings of the tenth ACM symposium on Access controlmodels and technologies, SACMAT ’05, pages 139–146, New York,NY, USA. ACM.
Yu, T., Winslett, M., and Seamons, K. E. (2003).
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