Análise Preliminar da Detecção de Ataques Ofuscados e do Uso de Hardware de Baixo Custo em um Sistema para Detecção de Ameaças
Abstract
Network traffic transmitted at high rates results in the need for more efficient security mechanisms, since analyzing package by package before taking an action becomes a costly task in terms of processing. One way to solve this problem is with the development and deployment of threat detection systems that use machine learning mechanisms to anticipate attacks. This paper presents the preliminary results obtained in an attempt to improve such a system by analyzing automated attacks that employ obfuscation and by evaluating the performance of a Raspberry Pi unit that can be used as a processing node in the improved system.
References
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Banzi, M. (2011). Getting Started with Arduino. Make: projects. O'Reilly Media.
Brown, S., Gommers, J., and Serrano, O. (2015). From Cyber Security Information Sha-ring to Threat Management. In Proceedings of the 2Nd ACM WISCS'15, pages 43-49.
Feth, D. (2015). User-centric Security: Optimization of the Security-usability Trade-off. In Proceedings of the 10th ESEC/FSE 2015, pages 1034-1037.
GT-BIS (2018). GT-BIS -Mecanismos para Análise de Big Data em Segurança da Informação. http://gtbis.ime.usp.br/. Último acesso em 22 de Março de 2019.
Pahl, C., Helmer, S., Miori, L., Sanin, J., and Lee, B. (2016). A Container-Based Edge Cloud PaaS Architecture Based on Raspberry Pi Clusters. In 4th IEEE FiCloudW, pages 117-124.
Raspberry Pi Foundation (2018). Raspberry Pi -Teach, Learn, and Make with Raspberry Pi. https://www.raspberrypi.org/. Último acesso em 22 de Março de 2019.
Singh, K. J. and Kapoor, D. S. (2017). Create Your Own Internet of Things: A survey of IoT Platforms. IEEE Consumer Electronics Magazine, 6(2):57-68.
Splunk (2019). SIEM, AIOps, Application Management, Log Management, Machine Learning, and Compliance -Splunk. https://www.splunk.com/en_us. Último acesso em 22 de Março de 2019.
Published
2019-05-06
How to Cite
OSHIRO, Lucas Seiki; BATISTA, Daniel Macêdo.
Análise Preliminar da Detecção de Ataques Ofuscados e do Uso de Hardware de Baixo Custo em um Sistema para Detecção de Ameaças. In: WORKSHOP ON SCIENTIFIC INITIATION AND GRADUATION - BRAZILIAN SYMPOSIUM ON COMPUTER NETWORKS AND DISTRIBUTED SYSTEMS (SBRC), 2. , 2019, Gramado.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 233-240.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc_estendido.2019.7792.
