Aplicação de Criptografia Homomórfica na Mineração de Dados em Fluxos de Roteadores de Borda na Internet
Abstract
Homomorphic Cryptography appears as a solution for data manipulation in a private preserving manner. On the other hand, the rising amount of data being daily generated makes Data Mining techniques more and more attractive. Therefore, this work has the creation of two methods for association rules generation for distributed databases as the objective, in a way that every participant mantains their share private. Real data extracted from Rede-Rio/FAPERJ’s backbone edge routers is used to validate the proposal.
References
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Fan, J. and Vercauteren, F. (2012). Somewhat practical fully homomorphic encryption. Cryptology ePrint Archive.
Frikken, K. (2007). Privacy-preserving set union. In ACNS, pages 237–252. Springer.
Gentry, C. (2009). A fully homomorphic encryption scheme. Stanford university.
Henry, K. J. (2008). The theory and applications of homomorphic cryptography. Master’s thesis, University of Waterloo.
Kaosar et al. (2012). Fully homomorphic encryption based two-party association rule mining. Data & Knowledge Engineering, 76:1–15.
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Taylor, P. (2022). Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2020, with forecasts from 2021 to 2025.
Badawi, A. A. et al. (2022). OpenFHE: Open-Source Fully Homomorphic Encryption Library. Cryptology ePrint Archive, Paper 2022/915.
Chakrabarti et al. (2006). Data mining curriculum: A proposal (Version 1.0). Intensive working group of ACM SIGKDD curriculum committee, 140:1–10.
de Assis et al. (2021). Iptraf: Coleta e detecção de anomalias em fluxos de rede. In Anais do XXVI Workshop de Gerência e Operação de Redes e Serviços, pages 96–109. SBC.
Fan, J. and Vercauteren, F. (2012). Somewhat practical fully homomorphic encryption. Cryptology ePrint Archive.
Frikken, K. (2007). Privacy-preserving set union. In ACNS, pages 237–252. Springer.
Gentry, C. (2009). A fully homomorphic encryption scheme. Stanford university.
Henry, K. J. (2008). The theory and applications of homomorphic cryptography. Master’s thesis, University of Waterloo.
Kaosar et al. (2012). Fully homomorphic encryption based two-party association rule mining. Data & Knowledge Engineering, 76:1–15.
Li, J. and Huang, H. (2020). Faster secure data mining via distributed homomorphic encryption. In 26th ACM SIGKDD, pages 2706–2714.
Mittal, D. et al. (2014). Secure data mining in cloud using homomorphic encryption. In CCE), pages 1–7. IEEE.
Taylor, P. (2022). Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2020, with forecasts from 2021 to 2025.
Published
2023-09-18
How to Cite
ASSIS, Felipe M. F. de; MACEDO, Evandro L. C.; MORAES, Luís F. M. de.
Aplicação de Criptografia Homomórfica na Mineração de Dados em Fluxos de Roteadores de Borda na Internet. In: WORKSHOP ON SCIENTIFIC INITIATION AND UNDERGRADUATE WORKS - BRAZILIAN SYMPOSIUM ON CYBERSECURITY (SBSEG), 23. , 2023, Juiz de Fora/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 273-278.
DOI: https://doi.org/10.5753/sbseg_estendido.2023.234236.
