Consenso Bizantino Baseado em uma Camada de Rede com Ordenação de Mensagens Tolerante a Intrusões
Resumo
Trabalhos recentes propuseram protocolos de consenso que dividem as tarefas de garantir as propriedades de acordo e de terminação entre as camadas de rede e de aplicação, respectivamente. A camada de rede precisa entregar as mensagens já ordenadas para garantir acordo. Para tanto, essas soluções normalmente utilizam um sequenciador. No entanto, tolerar um sequenciador malicioso traz novos desafios, uma vez que um mesmo número de sequência pode ser atribuído para diferentes mensagens e enviadas para diferentes réplicas. Para contornar tais problemas, o NeoBFT emprega um passo adicional de comunicação entre as réplicas. Apesar de lidar com o problema, essa abordagem impacta o desempenho do sistema, uma vez que sincronizações adicionais são necessárias nas réplicas antes da execução das requisições. Este trabalho propõe o NsoBFT (Network secure ordered BFT), um protocolo de consenso que utiliza uma camada de rede com um serviço seguro de ordenação de mensagens implementado através do componente seguro USIG (Unique Sequential Identifier Generator). Desta forma, não é necessário executar sincronizações adicionais nas réplicas antes de executar as requisições. Resultados experimentais comparam as propostas similares encontradas na literatura e mostram que esta característica faz com que o NsoBFT tenha um desempenho superior ao NeoBFT.
Palavras-chave:
Consenso, Algoritmos Distribuídos, Tolerância a Intrusões
Referências
Alchieri, E. A. P., Bessani, A., Greve, F., and Fraga, J. d. S. (2018). Knowledge connectivity requirements for solving Byzantine consensus with unknown participants. IEEE Transactions on Dependable and Secure Computing, 15(2), 246–259.
Bessani, A., Sousa, J., and Alchieri, E. E. P. (2014). State machine replication for the masses with BFT-SMaRt. In International Conference on Dependable Systems and Networks (pp. 355–362). IEEE.
Bravo, M., Chockler, G., and Gotsman, A. (2022). Making Byzantine consensus live. Distributed Computing, 35(6).
Castro, M. and Liskov, B. (1999). Practical Byzantine fault tolerance. In Symposium on Operating Systems Design and Implementation (pp. 173–186). Berkeley, CA, USA: USENIX.
Castro, M. and Liskov, B. (2002). Practical Byzantine fault-tolerance and proactive recovery. ACM Transactions on Computer Systems, 20(4), 398–461.
Douceur, J. R. (2002). The Sybil attack. In International Workshop on Peer-to-Peer Systems (pp. 251–260). Springer.
Dwork, C., Lynch, N. A., and Stockmeyer, L. (1988). Consensus in the presence of partial synchrony. Journal of ACM, 35(2), 288–322.
Fischer, M. J., Lynch, N. A., and Paterson, M. S. (1985). Impossibility of distributed consensus with one faulty process. Journal of the ACM, 32(2), 374–382.
Hadzilacos, V. and Toueg, S. (1994). A modular approach to the specification and implementation of fault-tolerant broadcasts. Technical report, Department of Computer Science, Cornell University, New York, USA.
Lamport, L. (1998). The part-time parliament. ACM Transactions on Computer Systems, 16(2), 133–169.
Lamport, L., Shostak, R., and Pease, M. (1982). The Byzantine generals problem. ACM Transactions on Programming Languages and Systems, 4(3), 382–401.
Li, C., Qiu, W., Li, X., Liu, C., and Zheng, Z. (2024). A dynamic adaptive framework for practical Byzantine fault tolerance consensus protocol in the Internet of Things. IEEE Transactions on Computers, 73(7), 1669–1682.
Li, J., Michael, E., Sharma, N. K., Szekeres, A., and Ports, D. R. (2016). Just say {NO} to Paxos overhead: Replacing consensus with network ordering. In Symposium on Operating Systems Design and Implementation (pp. 467–483). USENIX.
Liu, X. and Yu, W. (2024). A review of research on blockchain consensus mechanisms and algorithms. In International Conference on Intelligent Informatics and Biomedical Sciences, 9, 1–10.
Saramago, R. Q., Alchieri, E. A., Rezende, T. F., and Camargos, L. (2018). On the impossibility of Byzantine collision-fast atomic broadcast. In International Conference on Advanced Information Networking and Applications (pp. 414–421). IEEE.
Schneider, F. B. (1990). Implementing fault-tolerant services using the state machine approach: A tutorial. ACM Computing Surveys, 22(4), 299–319.
Singh, A., Kumar, G., Saha, R., Conti, M., Alazab, M., and Thomas, R. (2022). A survey and taxonomy of consensus protocols for blockchains. Journal of Systems Architecture, 127, 102503.
Sun, G., Jiang, M., Khooi, X. Z., Li, Y., and Li, J. (2023). NeoBFT: Accelerating Byzantine fault tolerance using authenticated in-network ordering. In ACM Special Interest Group on Data Communications Conference (pp. 239–254). New York, NY, USA: ACM.
Vassantlal, R., Alchieri, E., Ferreira, B., and Bessani, A. (2022). Cobra: Dynamic proactive secret sharing for confidential BFT services. In Symposium on Security and Privacy (pp. 1335–1353). IEEE.
Venâncio, G., Fulber-Garcia, V., Flauzino, J., Alchieri, E. A., and Duarte, E. P. (2024). Dependable virtual network services: An architecture for fault-and intrusion-tolerant SFCS. In Conference on NFV and SDN (pp. 1–6). IEEE.
Venâncio, G., Turchetti, R. C., and Duarte Jr, E. P. (2022). NFV-Coin: Unleashing the power of in-network computing with virtualization technologies. Journal of Internet Services and Applications, 13(1), 46–53.
Veronese, G. S., Correia, M., Bessani, A. N., Lung, L. C., and Verissimo, P. (2013). Efficient Byzantine fault-tolerance. IEEE Transactions on Computers, 62(1), 16–30.
Vukolić, M. (2015). The quest for scalable blockchain fabric: Proof-of-work vs. BFT replication. In IFIP WG 11.4 International Workshop Open Problems in Network Security (pp. 112–125). Springer.
White, B., Lepreau, J., Stoller, L., Ricci, R., Guruprasad, S., Newbold, M., Hibler, M., Barb, C., and Joglekar, A. (2002). An integrated experimental environment for distributed systems and networks. ACM SIGOPS Operating Systems Review, 36(SI), 255–270.
Zou, Y., Yang, L., Jing, G., Zhang, R., Xie, Z., Li, H., and Yu, D. (2024). A survey of fault tolerant consensus in wireless networks. High-Confidence Computing, 4(2), 100202.
Bessani, A., Sousa, J., and Alchieri, E. E. P. (2014). State machine replication for the masses with BFT-SMaRt. In International Conference on Dependable Systems and Networks (pp. 355–362). IEEE.
Bravo, M., Chockler, G., and Gotsman, A. (2022). Making Byzantine consensus live. Distributed Computing, 35(6).
Castro, M. and Liskov, B. (1999). Practical Byzantine fault tolerance. In Symposium on Operating Systems Design and Implementation (pp. 173–186). Berkeley, CA, USA: USENIX.
Castro, M. and Liskov, B. (2002). Practical Byzantine fault-tolerance and proactive recovery. ACM Transactions on Computer Systems, 20(4), 398–461.
Douceur, J. R. (2002). The Sybil attack. In International Workshop on Peer-to-Peer Systems (pp. 251–260). Springer.
Dwork, C., Lynch, N. A., and Stockmeyer, L. (1988). Consensus in the presence of partial synchrony. Journal of ACM, 35(2), 288–322.
Fischer, M. J., Lynch, N. A., and Paterson, M. S. (1985). Impossibility of distributed consensus with one faulty process. Journal of the ACM, 32(2), 374–382.
Hadzilacos, V. and Toueg, S. (1994). A modular approach to the specification and implementation of fault-tolerant broadcasts. Technical report, Department of Computer Science, Cornell University, New York, USA.
Lamport, L. (1998). The part-time parliament. ACM Transactions on Computer Systems, 16(2), 133–169.
Lamport, L., Shostak, R., and Pease, M. (1982). The Byzantine generals problem. ACM Transactions on Programming Languages and Systems, 4(3), 382–401.
Li, C., Qiu, W., Li, X., Liu, C., and Zheng, Z. (2024). A dynamic adaptive framework for practical Byzantine fault tolerance consensus protocol in the Internet of Things. IEEE Transactions on Computers, 73(7), 1669–1682.
Li, J., Michael, E., Sharma, N. K., Szekeres, A., and Ports, D. R. (2016). Just say {NO} to Paxos overhead: Replacing consensus with network ordering. In Symposium on Operating Systems Design and Implementation (pp. 467–483). USENIX.
Liu, X. and Yu, W. (2024). A review of research on blockchain consensus mechanisms and algorithms. In International Conference on Intelligent Informatics and Biomedical Sciences, 9, 1–10.
Saramago, R. Q., Alchieri, E. A., Rezende, T. F., and Camargos, L. (2018). On the impossibility of Byzantine collision-fast atomic broadcast. In International Conference on Advanced Information Networking and Applications (pp. 414–421). IEEE.
Schneider, F. B. (1990). Implementing fault-tolerant services using the state machine approach: A tutorial. ACM Computing Surveys, 22(4), 299–319.
Singh, A., Kumar, G., Saha, R., Conti, M., Alazab, M., and Thomas, R. (2022). A survey and taxonomy of consensus protocols for blockchains. Journal of Systems Architecture, 127, 102503.
Sun, G., Jiang, M., Khooi, X. Z., Li, Y., and Li, J. (2023). NeoBFT: Accelerating Byzantine fault tolerance using authenticated in-network ordering. In ACM Special Interest Group on Data Communications Conference (pp. 239–254). New York, NY, USA: ACM.
Vassantlal, R., Alchieri, E., Ferreira, B., and Bessani, A. (2022). Cobra: Dynamic proactive secret sharing for confidential BFT services. In Symposium on Security and Privacy (pp. 1335–1353). IEEE.
Venâncio, G., Fulber-Garcia, V., Flauzino, J., Alchieri, E. A., and Duarte, E. P. (2024). Dependable virtual network services: An architecture for fault-and intrusion-tolerant SFCS. In Conference on NFV and SDN (pp. 1–6). IEEE.
Venâncio, G., Turchetti, R. C., and Duarte Jr, E. P. (2022). NFV-Coin: Unleashing the power of in-network computing with virtualization technologies. Journal of Internet Services and Applications, 13(1), 46–53.
Veronese, G. S., Correia, M., Bessani, A. N., Lung, L. C., and Verissimo, P. (2013). Efficient Byzantine fault-tolerance. IEEE Transactions on Computers, 62(1), 16–30.
Vukolić, M. (2015). The quest for scalable blockchain fabric: Proof-of-work vs. BFT replication. In IFIP WG 11.4 International Workshop Open Problems in Network Security (pp. 112–125). Springer.
White, B., Lepreau, J., Stoller, L., Ricci, R., Guruprasad, S., Newbold, M., Hibler, M., Barb, C., and Joglekar, A. (2002). An integrated experimental environment for distributed systems and networks. ACM SIGOPS Operating Systems Review, 36(SI), 255–270.
Zou, Y., Yang, L., Jing, G., Zhang, R., Xie, Z., Li, H., and Yu, D. (2024). A survey of fault tolerant consensus in wireless networks. High-Confidence Computing, 4(2), 100202.
Publicado
19/05/2025
Como Citar
DA ROCHA, Gabriel Faustino Lima; ALCHIERI, Eduardo A. P.; VENÂNCIO, Giovanni; FULBER-GARCIA, Vinicius; DUARTE JR., Elias P..
Consenso Bizantino Baseado em uma Camada de Rede com Ordenação de Mensagens Tolerante a Intrusões. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 43. , 2025, Natal/RN.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 532-545.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2025.6309.
