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Peer-to-Peer Systems and Blockchain

Code UE : USEET4

  • Cours
  • 5 crédits

Responsable(s)

Stefano SECCI

Public, conditions d’accès et prérequis

  • Computer Networks.  
  • At least one programming language. 
  • Algorithmics. 

Objectifs pédagogiques

The student will acquire knowledge relative to the development of distributed systems, in particular of blockchain-based systems. 
At the end of the course, the student 
  • will be able to develop a distributed application. 
  • will be able to develop a smart contract. 
  • will be able to understand consensus mechanisms. 

Contenu

The course covers the following topics: 
  • Peer-to-peer Systems: general concepts, unstructured overlays: Flooding, Random Walks, Epidemic Diffusion, structured overlays: Distributed Hash Tables (DHT), Routing on a DHT, IPFS. 
  • Blockchains: basic concepts, basic cryptographic tools (digital signatures, cryptographic hash, Zero-Knowledge,..), data structures: Merkle trees, Merkle Patricia tries.  
  • Bitcoin: transaction and block structure.  Mining : Proof of Work, rewards. Bitcoin: attacks, 51%, double spending. Bitcoin: tracciabilità e mixing. Structure of the P2P network. 
  • Bizantine Fault-Tolerance (BFT) Consensus and BFT-based blockchains. 
  • Ethereum: smart contract, gas. Consensus: from PoW to PoS. Ethereum: Solidity, smart contracts programming. Smart contract security and attacks. 
  • Distributed Ledgers Applications: tokens (fungible and non-fungible), Self Sovereign Identity, Supply-chains. 
  • Scalability enhancement: Zero Knowledge rollup e optimistic roll-up, side chain, inter-chain protocols, channel networks (Lightning network). 
  complementary content:  
  • Peer to peer system: applications BitTorrent, a Content Distribution Network, implementation of the Kademlia  DHT.  

Modalité d'évaluation

At the end of the course, the student must submit the final project to be evaluated. 

Cette UE apparaît dans les diplômes et certificats suivants

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Intitulé de la formation
Type
Modalité(s)
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Intitulé de la formation Artificial Intelligence for Connected Industries
Type Diplôme national (DEUST, licence, master, doctorat, diplôme d'Etat)
Lieu(x) Package
Lieu(x) Paris
Entrée Niveau 6 (Bac+3 et 4)
Intitulé de la formation Type Modalité(s) Lieu(x)

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