A Fuzzy Inference System for DDoS Identification in Fog Computing based on Energy Consumption

Authors

DOI:

https://doi.org/10.5753/jisa.2025.5161

Keywords:

Fog Computing, Energy Consumption, Distributed Denial of Service Attack, Fuzzy Logic

Abstract

Internet of Things (IoT) networks, characterized by their heterogeneous devices, standards, and features, along with limited energy resources, are particularly vulnerable to security threats. Fog computing, which processes data closer to the network edge (i.e., IoT devices), has emerged as a key paradigm for addressing these issues. The Message Queuing Telemetry Transport (MQTT) protocol is commonly used for communication between IoT and fog devices due to its simplicity and ease of implementation. However, MQTT does not include built-in security measures, making it susceptible to Distributed Denial of Service (DDoS) attacks. This paper identifies the main DDoS threats in the context of the MQTT protocol and proposes a Fuzzy Inference System (FIS) designed to detect and classify specific DDoS attack types. By analyzing energy consumption patterns in fog nodes, fuzzy logic infers the degree of membership of a DDoS attack in a fog node, providing a robust method for threat detection in IoT environments.

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Author Biographies

Diogo Vinicius Martins da Cruz, Universidade Tecnológica Federal do Paraná

Possui mestrado em Computação Aplicada (2021) pelo Programa de Pós-Graduação em Computação Aplicada (PPGCA) e especialização em Redes de Computadores e Teleinformática (2017), ambos pela Universidade Tecnológica Federal do Paraná (UTFPR). Possui graduação em Sistemas de Informação (2013) pela Universidade Maurício de Nassau. É professor do SENAI, PR, corretor de atividades EAD pela UNINTER e Militar do Exército Brasileiro. Possui experiência em servidores Linux.

Ana Cristina Barreiras Kochem Vendramin, Universidade Tecnológica Federal do Paraná

Ana Cristina Barreiras Kochem Vendramin is a full professor in the Academic Department of Informatics (DAINF) and the Graduate Program in Applied Computing (PPGCA) at the Federal University of Technology – Paraná (UTFPR), Curitiba, Brazil. She received her Master of Science in Telematics (2003) and her Ph.D. in Computer Engineering (2012) from the Graduate Program in Electrical and Computer Engineering (CPGEI) at UTFPR. Her research interests include Computer Networks, Distributed Systems, and Computational Intelligence.

Daniel Fernando Pigatto, Universidade Tecnológica Federal do Paraná

Professor no Departamento Acadêmico de Informática (DAINF) e no Programa de Pós-Graduação em Computação Aplicada (PPGCA) da Universidade Tecnológica Federal do Paraná (UTFPR), campus Curitiba, desde 2017. Possui título de Bacharel em Ciência da Computação pela Universidade Regional Integrada (URI), Câmpus Erechim, RS (2009) e títulos de Mestre (2012) e de Doutor (2017) em Ciências no Programa de Ciências de Computação e Matemática Computacional (CCMC) do Instituto de Ciências Matemáticas e de Computação (ICMC) da Universidade de São Paulo (USP), Câmpus São Carlos, SP. Realizou doutorado-sanduíche (2015) na University of the West of England (UWE), Bristol, Reino Unido. Coordena o projeto de extensão "Cafezíneos Blog, Live e Podcast - Discutindo a Universidade", que visa a divulgação da universidade por meio de redes sociais, vídeos, textos e podcasts. É coordenador do Prorama de Pós-graduação em Computação Aplicada (PPGCA) desde 2023. É pesquisador na área de Redes de Computadores com destaque para Computação em Névoa, Internet das Coisas, Segurança, Sistemas Embarcados Críticos, Veículos Aéreos Não Tripulados e Avaliação de Desempenho de Sistemas Computacionais.

Juliana de Santi, Universidade Tecnológica Federal do Paraná

Juliana de Santi received her B.Sc. in Informatics from the University of Western Paraná in 2004 and her M.Sc. (2008) and Ph.D. (2015) in Computer Science from the University of Campinas. Since 2015, she has served as an Assistant Professor in the Department of Informatics at the Federal University of Technology - Paraná (UTFPR), Brazil. Her main research areas are optical networks and cybersecurity.

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Published

2025-05-21

How to Cite

da Cruz, D. V. M., Vendramin, A. C. B. K., Pigatto, D. F., & de Santi, J. (2025). A Fuzzy Inference System for DDoS Identification in Fog Computing based on Energy Consumption. Journal of Internet Services and Applications, 16(1), 209–223. https://doi.org/10.5753/jisa.2025.5161

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Vol. 16 No. 1 (2025)

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Research article

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