Dr. Önder Gürcanonder.gurcan@cea.fr

Trustworthy, Smart and Self-Organizing Information Systems LaboratoryCEA LIST

Internship Opportunities on Blockchainsat the CEA LIST

25.09.2019

CEA, from research to industryFrench 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

ÖnderGurcan

AgnèsLanusse

Francois Le Fevre

YackholleyAmoussou

Sara TucciHead of the Lab

5

Anatomy of a Blockchain

0 1

$

2

$

… 48

$

49

$

50

$

49

$

51

$

GenesisBlock

BlockchainHead

ForkSide chain

Main chain

StaleBlock

Block Creator P

Block Creator M

height = 51

67%

33%

Blocks in the blockchain

P MQuality ofthe chain

Limitedsize

Blockchain Systems

• Open, dynamic and distributed system

• Social and economicalsystem

• Multiple heterogeneouslayers/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 - ConfederatedInternational 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 objective is

• rapid prototyping of industrial cases, and

• feasibility analysis in a realisticmanner.

• MAX

• is a modular framework for agent-based simulation,

• is based on the Agent/Environment/Rolearchitecture,

• allows automated testing of models.Simulation

Engine

NetworkModel

Generic Blockchain ModelBlockchain

Abstract Datatypes

Bitcoin Model(compatible with github)

Tendermint Model(compatible with [1])

BitcoinLightning

Tender.Fairness

Tender.Byzantine

Consensus Oracle [2] (PoX, PBFT)

AnotherModel

Broadcast Network

Model

p2p Network

Model

Automated Testing [3]

AgentEnvironment

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.

AnotherBlockchain

AnotherModel

incentives

Internship 1: Fair BlockchainContext: So far there are few works addressing the fairness problem or tryfind any solutions.

In particual, FairLedger [1], one of the first (committee-based) blockchain thataddresses fairness to users, however limited by strong assumptions about thesystem model.

Objective: The objective of this internship is to design a new Blockchainsolution starting from FairLedger and implement a simplified version of it inMAX (modifying one of the existing blockchains implemented in thesimulator), 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 aremore than two blocks appended to the same block (fork).To prevent this, Bitcoin uses the Proof of Work mechanism. However, even if withsmall probability, Proof of Work allows forks. For this reason, it is not suitable forblockchain aiming at providing strong consistency properties.Tendermint is a consensus based blockchain. The crucial point in Tendermint is thecomposition of the committee (selected among the system participants) thatexecutes the Consensus algorithm to guarantee the absence of forks, indeedeverything works under the assumption that the fraction of attackers in thecommittee is bounded. If not, forks may occur.Objective: The objective of this internship is to first modify the existingTendermint 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 improvethe pre-detection capability.

Internship 3: Reinforcement Learning forFairness in Blockchains

Context: Up until now, LICIA has shown by mathematical analyses thatBitcoin (PoW) and Tendermint (committee-based) blockchains are unfair toits participants considering the closed system assumption.

During all these studies, various rational agent strategies and rewardingmechanisms have been proposed.

Objective: To develop a reinforcement learning (RL) model for finding thebest strategies resulting fairness in blockchains and to study the implicationsof 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 bede- fined and developed for rational agents to build a reinforcement learningmodel for fairness.

Internship 4: Development of a Web Extension for Multi-Agent eXperimenter

Context: For the moment, MAX runs as a standard Java graphics andconsole 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 thefunctionalities of the web portal will be defined. Next, a series of REST services that allowdefining and executing blockchain simulation experiments using the agent-basedabstraction will be developed. To create dashboards to visualize the data the ELK Stackwill be used. Finally, the practicality of the web extension will be demonstrated on apayment system the access of simulation services, such as the smart-contract auditplatform myThx, and on the other hand to notarize the results of a MAX simulationdirectly 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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