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Dynamic Role Binding in Blockchain-Based
Collaborative Business Processes
Orlenys López-Pintado
Marlon Dumas, Luciano García-Bañuelos, Ingo
Weber
University of Tartu, Estonia
Data61, CSIRO, Australia
June 6, 2019
2
Introduction
Alice
Alice’s Company
Business Process
Management System
(BPMS)
Alice’s Employees
Access Control
3
Introduction
Alice’s company Bob’s company
Purchase
Goods
Ship
Goods
Carrier
Collaborative Process
Role Based Access Control (RBAC)?
4
Problem
Alice’s company Bob’s company
Purchase
Goods
Ship
Goods
Carrier
Carrier
Carol’s company
TRUS
T
Alice
Bob
Collaborative Process
5
Problem
Alice’s company Bob’s company
Purchase
Goods
Ship
Goods
Carrier
LACK OF TRUST
Collaborative Process
ACTORS CHANGE DYNAMICALLY
TRUST RELATIONS CHANGE
DYNAMICALLY
Dave’s company Carol’s companyWendy’s company
6
Background & Related Work
BLOCKCHAIN
P2P Network No Central Authority
Untrusted Parties
Append only chain
Each node stores a copy
Consensus
Validate Transactions
Create/Validate Blocks
Proof of Work
Smart Contracts
Blockchain-based Process Management Tools
Lorikeet
Caterpillar Mainly Control-Flow
Static Access Control
DYNAMIC BINDINGS
7
Background & Related
WorkBinding/Delegation Models for Collaborative Processes
* Web Service Composition
- Partner links
- Process orchestrated by a single entity
- Business Process Execution Language
(BPEL)
* Process not orchestrated by a single entity
- Each role controlled by a single actor
- Re-biding not supported
* Delegation/Revocation schemas
TRUST
DYNAMIC ROLE BINDING IN DECENTRALIZED
PROCESSES,
MULTIPLE ACTORS MUST COLLABORATIVELY
AGREE
DURING THE PROCESS EXECUTION (AT RUNTIME)
DYNAMIC BINDINGS
What to do ?
8
Role Binding Model
Customer Supplier
Task * 1 Role
Role 1 1 Actor per (sub-)process instance
 All assignments in sub-scopes stored
in a set
User Group
System
IoT
Blockchain
Account/identity
9
Binding Policy Specification
Customer Supplier
Supplier Candidate Carrier
Under Shipment, Supplier nominates Candidate;
Under Shipment, Supplier nominates Carrier in Candidate endorsed-by Customer;
Nominator
Policy Statement Operations
Nominee
Binding Constraint
nominate
release
vote
Endorsement Constraint
Customer is case-creator;
Customer nominates Supplier;
10
Role Lifecycle
UNBOUND
NOMINATE
D
RELEASIN
G
BOUND
Nominate(E)
Nominate(!E)
Vote
(E not satisfied)
Vote
(E satisfiable)
Vote
(E satisfied)
Release(!E)
Release(E)
Vote
(E not satisfied)
Vote
(E satisfiable)
Vote
(E satisfied)
11
Policy Consistency
N E
A is case-creator;
A nominates B;
A nominates C;
C nominates D, endorsed-by A and B;
uA nA bA
N E
uB nB bB
N E
uC nC bC
N E
uD nD bD
A & B
N
N
E
E
N
A & B
E
NO DEADLOCKS
12
Smart Contract Generation
Policy Compiler Caterpillar Compiler
Worklist Handler
BindingPolicy
TaskRoleMap
BindingAccessControl
canNominate
Nominator (Supplier) index 3,
nMask (nominees {Candidate, Carrier}) = 6 [00000110]
assertNConstraint
(A and B) or (C) or ..,
Bit Sets
13
Smart Contract Generation
Policy Compiler
BindingPolicy
assertNVote
Bit Sets
BOUND if all the roles in at least a conjunction set, namely CS,
endorsed the nomination, i.e., (endorsedBy | endorserRole) & CS == CS,
UNBOUND if in each conjunction set contains at least one role rejected
the nomination, i.e., for each CS, (rejectedBy | endorserRole) & CS != 0
Conjunction set: A and B and …
NOMINATED if none of the previous conditions are fulfilled yet, i.e.,
at least one conjunction set with no rejections and roles pending to
vote
14
Experiments
How does the cost (in gas/ether) of enforcing a binding policy increase
depending on the size and complexity of the policy statements?
1. How do the costs of deploying the generated smart contracts vary
with the size of the policy?
2. How do the costs of executing the runtime operations vary
with the size of the policy?
3. How does the combined cost of enforcing a process model and a
binding policy varies with the size of the model?
15
Experiments
Experiments vary different parameters:
• E1: Varied number of nomination statements from 1 to 40; no
binding or endorsement constraints.
• E2: 40 statements, pick one, and gradually increased the size of the
conjunction set in its binding constraint from 1 to 40
• E3: 40 statements, then gradually add a binding constraint with one
conjunction set to each of the 40 statements.
• E4: 40 statements, pick one, and gradually increased the size of the
conjunction set in its endorsement constraint from 1 to 40
• E5: 40 statements, then gradually add an endorsement constraint
with one conjunction set to each of the 40 statements.
16
Experiment Results
0
200000
400000
600000
800000
1000000
1200000
1 4 7 10 13 16 19 22 25 28 31 34 37
GasCost
Number of statements/conjunction sets
E1
E2
E3
E4
E5
1. How do the costs of deploying the generated smart contracts vary
with the size of the policy?
17
Experiment Results
2. How do the costs of executing the runtime operations vary with the
size of the policy?
3. How does the combined cost of enforcing a process model and a
binding policy varies with the size of the model?
BindingAccessControl: 1,340,098 gas
BindingPolicy: 154,167 to 1,803,898
gasTaskRoleMap: 129,539 to 241,114 gas
18
Conclusion
Role Binding Model and a Binding Policy Language that support
collaborative binding and unbinding of actors to roles at runtime.
Method to verify the consistency of policies.
Approach to compile the policies into smart contracts.
Access Control implemented in Caterpillar (open source).
Experiments (throughput): costs grow linearly with the number of
roles and the complexity of the constraints.
Future Work Validate the approach via more
thorough experiments and case studies.
Study the applicability of this approach to other blockchain applications,
e.g. in crowdsourcing and computer-supported collaborative work
scenarios
Questions
THANK
YOU

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Dynamic Role Binding in Blockchain-Based Collaborative Business Processes

  • 1. Dynamic Role Binding in Blockchain-Based Collaborative Business Processes Orlenys López-Pintado Marlon Dumas, Luciano García-Bañuelos, Ingo Weber University of Tartu, Estonia Data61, CSIRO, Australia June 6, 2019
  • 2. 2 Introduction Alice Alice’s Company Business Process Management System (BPMS) Alice’s Employees Access Control
  • 3. 3 Introduction Alice’s company Bob’s company Purchase Goods Ship Goods Carrier Collaborative Process Role Based Access Control (RBAC)?
  • 4. 4 Problem Alice’s company Bob’s company Purchase Goods Ship Goods Carrier Carrier Carol’s company TRUS T Alice Bob Collaborative Process
  • 5. 5 Problem Alice’s company Bob’s company Purchase Goods Ship Goods Carrier LACK OF TRUST Collaborative Process ACTORS CHANGE DYNAMICALLY TRUST RELATIONS CHANGE DYNAMICALLY Dave’s company Carol’s companyWendy’s company
  • 6. 6 Background & Related Work BLOCKCHAIN P2P Network No Central Authority Untrusted Parties Append only chain Each node stores a copy Consensus Validate Transactions Create/Validate Blocks Proof of Work Smart Contracts Blockchain-based Process Management Tools Lorikeet Caterpillar Mainly Control-Flow Static Access Control DYNAMIC BINDINGS
  • 7. 7 Background & Related WorkBinding/Delegation Models for Collaborative Processes * Web Service Composition - Partner links - Process orchestrated by a single entity - Business Process Execution Language (BPEL) * Process not orchestrated by a single entity - Each role controlled by a single actor - Re-biding not supported * Delegation/Revocation schemas TRUST DYNAMIC ROLE BINDING IN DECENTRALIZED PROCESSES, MULTIPLE ACTORS MUST COLLABORATIVELY AGREE DURING THE PROCESS EXECUTION (AT RUNTIME) DYNAMIC BINDINGS What to do ?
  • 8. 8 Role Binding Model Customer Supplier Task * 1 Role Role 1 1 Actor per (sub-)process instance  All assignments in sub-scopes stored in a set User Group System IoT Blockchain Account/identity
  • 9. 9 Binding Policy Specification Customer Supplier Supplier Candidate Carrier Under Shipment, Supplier nominates Candidate; Under Shipment, Supplier nominates Carrier in Candidate endorsed-by Customer; Nominator Policy Statement Operations Nominee Binding Constraint nominate release vote Endorsement Constraint Customer is case-creator; Customer nominates Supplier;
  • 10. 10 Role Lifecycle UNBOUND NOMINATE D RELEASIN G BOUND Nominate(E) Nominate(!E) Vote (E not satisfied) Vote (E satisfiable) Vote (E satisfied) Release(!E) Release(E) Vote (E not satisfied) Vote (E satisfiable) Vote (E satisfied)
  • 11. 11 Policy Consistency N E A is case-creator; A nominates B; A nominates C; C nominates D, endorsed-by A and B; uA nA bA N E uB nB bB N E uC nC bC N E uD nD bD A & B N N E E N A & B E NO DEADLOCKS
  • 12. 12 Smart Contract Generation Policy Compiler Caterpillar Compiler Worklist Handler BindingPolicy TaskRoleMap BindingAccessControl canNominate Nominator (Supplier) index 3, nMask (nominees {Candidate, Carrier}) = 6 [00000110] assertNConstraint (A and B) or (C) or .., Bit Sets
  • 13. 13 Smart Contract Generation Policy Compiler BindingPolicy assertNVote Bit Sets BOUND if all the roles in at least a conjunction set, namely CS, endorsed the nomination, i.e., (endorsedBy | endorserRole) & CS == CS, UNBOUND if in each conjunction set contains at least one role rejected the nomination, i.e., for each CS, (rejectedBy | endorserRole) & CS != 0 Conjunction set: A and B and … NOMINATED if none of the previous conditions are fulfilled yet, i.e., at least one conjunction set with no rejections and roles pending to vote
  • 14. 14 Experiments How does the cost (in gas/ether) of enforcing a binding policy increase depending on the size and complexity of the policy statements? 1. How do the costs of deploying the generated smart contracts vary with the size of the policy? 2. How do the costs of executing the runtime operations vary with the size of the policy? 3. How does the combined cost of enforcing a process model and a binding policy varies with the size of the model?
  • 15. 15 Experiments Experiments vary different parameters: • E1: Varied number of nomination statements from 1 to 40; no binding or endorsement constraints. • E2: 40 statements, pick one, and gradually increased the size of the conjunction set in its binding constraint from 1 to 40 • E3: 40 statements, then gradually add a binding constraint with one conjunction set to each of the 40 statements. • E4: 40 statements, pick one, and gradually increased the size of the conjunction set in its endorsement constraint from 1 to 40 • E5: 40 statements, then gradually add an endorsement constraint with one conjunction set to each of the 40 statements.
  • 16. 16 Experiment Results 0 200000 400000 600000 800000 1000000 1200000 1 4 7 10 13 16 19 22 25 28 31 34 37 GasCost Number of statements/conjunction sets E1 E2 E3 E4 E5 1. How do the costs of deploying the generated smart contracts vary with the size of the policy?
  • 17. 17 Experiment Results 2. How do the costs of executing the runtime operations vary with the size of the policy? 3. How does the combined cost of enforcing a process model and a binding policy varies with the size of the model? BindingAccessControl: 1,340,098 gas BindingPolicy: 154,167 to 1,803,898 gasTaskRoleMap: 129,539 to 241,114 gas
  • 18. 18 Conclusion Role Binding Model and a Binding Policy Language that support collaborative binding and unbinding of actors to roles at runtime. Method to verify the consistency of policies. Approach to compile the policies into smart contracts. Access Control implemented in Caterpillar (open source). Experiments (throughput): costs grow linearly with the number of roles and the complexity of the constraints. Future Work Validate the approach via more thorough experiments and case studies. Study the applicability of this approach to other blockchain applications, e.g. in crowdsourcing and computer-supported collaborative work scenarios