Trabajo Fin de Máster
Reputation-Based Consensus on a Secure Blockchain Network
Autor/es | Marín Fernández, Emilio |
Director | Maestre Torreblanca, José María |
Departamento | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática |
Fecha de publicación | 2020 |
Fecha de depósito | 2020-08-17 |
Titulación | Universidad de Sevilla. Master en Ingeniería Industrial |
Resumen | The aim of this thesis is to research new algorithms of consensus for distributed systems and running these
consensus within a secure blockchain network built with Hyperledger Fabric allowing a full traceability
of ... The aim of this thesis is to research new algorithms of consensus for distributed systems and running these consensus within a secure blockchain network built with Hyperledger Fabric allowing a full traceability of transactions and audit of the process. We will describe every detail involved in the creation of a blockchain network, from the main concepts to developing a production-ready network with identity management and multiple nodes. Using Hyperledger Fabric and Composer we will be able to create simple and complex networks that will be reachable from any client through a REST API. A new reputation-based consensus algorithm will be proposed taking full advantage of the blockchain technology. Each participant of the network will have a reputation level that increases or decreases depending on their behavior with the rest of the network. In every consensus round there’s a verification phase within the blockchain smart contracts that would decide the reputation delta of each participant. With everything developed we will compare the proposed algorithm with others learned in the literature in different scenarios such as when malicious agents try to prevent the consensus being reached or generating an error in the agreed value, we will study the speed, value offset and convergence. |
Cita | Marín Fernández, E. (2020). Reputation-Based Consensus on a Secure Blockchain Network. (Trabajo Fin de Máster Inédito). Universidad de Sevilla, Sevilla. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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TFM-1662-MARIN FERNANDEZ.pdf | 3.788Mb | [PDF] | Ver/ | |