Dr. Önder Gürcan [email protected]
Trustworthy, Smart and Self-Organizing Information Systems Laboratory CEA LIST
Internship Opportunities on Blockchains at the CEA LIST
25.09.2019
CEA, from research to industry
French Alternative Energies and Atomic Energy Commission
CEA is not only Atomic Energy
Where are we?
Laboratory for Trustworthy, Smart and
Self-Organizing Information Systems (LICIA)
Antonella Del Pozzo Önder
Gurcan Agnès
Lanusse Francois Le Fevre
Yackholley Amoussou
Sara Tucci
Head of the Lab
5
Anatomy of a Blockchain
0 1
$
2
$
… 48
$
49
$
50
$
49
$
51
$ Genesis
Block
Blockchain Head
Fork
Side chain
Main chain
Stale Block
Block Creator P
Block Creator M
height = 51
67%
33%
Blocks in the blockchain
P M Quality of
the chain Limited
size
Blockchain Systems
• Open, dynamic and distributed system
• Social and economical system
• Multiple heterogeneous layers/environments and multiple roles
• Intelligence can be added!
Discover How MAX can Help Your Organization Harness the Power of Blockchains @ Önder GÜRCAN (CEA LIST)
25/09/2019 6
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OPEN PROBLEMS on Blockchains
• Protocol related
• Reliability (correctness, consistency …),
• Security (privacy, confidentiality…),
• Performance (scalability …)
• …
• Participant related
• Incentives,
• Fairness,
• …
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FAIRNESS in Blockchain Systems
• What is fairness?
• Satisfaction of the participants from the system.
• Why is fairness important?
• Satisfied participants -> tend to stay in the system
• Unsatisfied participants -> tend to leave the system
• # of participants -> security and stability
• It is complex to achieve in all kinds of blockchains:
• Bitcoin is not fair to its users [3, 4],
• IOTA – a DAG-based blockchain – is not fair [2],
• Tendermint – a committee-based blockchain – is not fair [1].
[1] Y. Amoussou-Guenou, A. del Pozzo, M. Potop-Butucaru, and S. Tucci-Piergiovanni, Correctness and Fairness of Tendermint-core Blockchains, Technical Report, 2018.
[2] G. Bu, Ö. Gürcan, and M. Potop-Butucaru, G-IOTA: Fair and confidence aware tangle, in IEEE INFOCOM WORKSHOPS, 2019.
[3] Ö. Gürcan, A. D. Pozzo, and S. Tucci Piergiovanni, On the Bitcoin Limitations to Deliver Fairness to Users, in OTM 2017 Conferences - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2017, Rhodes, Greece, October 23-27, 2017, Proceedings, Part I, 2017, pp. 589–606.
[4] Ö. Gürcan, A. R. Pedrosa, and S. Tucci Piergiovanni, On Cancellation of Transactions in Bitcoin-like Blockchains, in OTM 2018 Conferences - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2018, Rhodes, Greece, October 24-28, 2018, Proceedings, Part I, 2018, pp. 516–533.
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However, it is even MORE COMPLEX …
[1] Ö. Gürcan, Multi-Agent Modelling of Fairness for Users and Miners in Blockchains, in Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems.
The PAAMS Collection, 2019, pp. 92–99.
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MAX: Multi-Agent eXperimenter
• the objectiveis
• rapid prototypingof industrial cases, and
• feasibility analysisin a realistic manner.
• MAX
• is a modular frameworkfor agent-based simulation,
• is based on the
Agent/Environment/Role architecture,
• allows automated testingof models.
Simulation Engine Network
Model
Generic Blockchain Model Blockchain Abstract Datatypes
Bitcoin Model
(compatible with github) Tendermint Model
(compatible with [1])
Bitcoin
Lightning FairnessTender. ByzantineTender.
Consensus Oracle [2]
(PoX, PBFT)
Another Model
Broadcast Network
Model p2p
Network Model
Automated Testing [3]
Agent Environment
Role
[1] Y. Amoussou-Guenou, A. Del Pozzo, M. Potop-Butucaru, and S. Tucci-Piergiovanni, Dissecting Tendermint, International Conference on Networked Systems (NETYS 2019), pp 166-182, 2019.
[2] E. Anceaume, A. Del Pozzo, R. Ludinard, M. Potop-Butucaru, and S. Tucci-Piergiovanni, Blockchain Abstract Data Type, in SPAA 2019, Phoenix, AZ, USA, June 22-24, 2019., 2019, pp. 349–358.
[3] Ö. Gürcan, O. Dikenelli, C. Bernon (2013). A generic testing framework for agent-based simulation models. Journal of Simulation.
Another Blockchain
Another Model
incentives
Internship 1: Fair Blockchain
Context: So far there are few works addressing the fairness problem or try find any solutions.
In particual, FairLedger [1], one of the first (committee-based) blockchain that addresses fairness to users, however limited by strong assumptions about the system model.
Objective: The objective of this internship is to design a new Blockchain solution starting from FairLedger and implement a simplified version of it in MAX (modifying one of the existing blockchains implemented in the simulator), in order to assess the validity of the proposed solution.
[1] Kfir Lev-Ari, Alexander Spiegelman, Idit Keidar, Dahlia Malkhi, FairLedger: A Fair Blockchain Protocol for Financial Institutions, arXiv, 2019.
Internship 2: Fork pre-detection in consensus based blockchains
Context: To preserve the chain shape it should never happen that there are more than two blocks appended to the same block (fork).
To prevent this, Bitcoin uses the Proof of Work mechanism. However, even if with small probability, Proof of Work allows forks. For this reason, it is not suitable for blockchain aiming at providing strong consistency properties.
Tendermint is a consensus based blockchain. The crucial point in Tendermint is the composition of the committee (selected among the system participants) that executes the Consensus algorithm to guarantee the absence of forks, indeed everything works under the assumption that the fraction of attackers in the committee is bounded. If not, forks may occur.
Objective: The objective of this internship is to first modify the existing Tendermint solution (in MAX) to derive conclusions about the possibility of pre- detecting forks (observing the messages exchanged) before that such fork occurs.
Secondly, to modify the information exchanged by processes in order to improve the pre-detection capability.
Internship 3: Reinforcement Learning for Fairness in Blockchains
Context: Up until now, LICIA has shown by mathematical analyses that Bitcoin (PoW) and Tendermint (committee-based) blockchains are unfair to its participants considering the closed system assumption.
During all these studies, various rational agent strategies and rewarding mechanisms have been proposed.
Objective: To develop a reinforcement learning (RL) model for finding the best strategies resulting fairness in blockchains and to study the implications of the developed model through computer experimentations using MAX.
To this end, together with the existing strategies and rewarding mechanisms,
new utility functions, new strategies and new rewarding mechanisms will be
de- fined and developed for rational agents to build a reinforcement learning
model for fairness.
Internship 4: Development of a Web
Extension for Multi-Agent eXperimenter
Context: For the moment, MAX runs as a standard Java graphics and
console application and to allow a greater number of users, a prototype web portal has been created based on the JHispter framework.
Objective: To develop a web extension for the MAX platform.
To this end, an agile methodology will be set up and firstly the specifications related to the functionalities of the web portal will be defined. Next, a series of REST services that allow defining and executing blockchain simulation experiments using the agent-based abstraction will be developed. To create dashboards to visualize the data the ELK Stack will be used. Finally, the practicality of the web extension will be demonstrated on a payment system the access of simulation services, such as the smart-contract audit platform myThx, and on the other hand to notarize the results of a MAX simulation directly in a blockchain, such as Ethereum.
Competences
1. Being Master 2 in Computer Science/Engineering.
2. Knowledge about distributed systems and/or multi-agent systems in general.
3. Knowledge about the blockchain technology is a plus.
4. Good experience in programming in any object-oriented language.
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