IoT Botnet Detection Based on the Behaviors of DNS Queries

Fan, Chun-I; Shie, Cheng-Han; Hsu, Chun‐Wei; Ban, Tao; Morikawa, Tomohiro; Takahashi, Takeshi

doi:10.1109/dsc54232.2022.9888913

2022 IEEE Conference on Dependable and Secure Computing (DSC) 2022

DOI: 10.1109/dsc54232.2022.9888913

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IoT Botnet Detection Based on the Behaviors of DNS Queries

Chun-I Fan

Cheng-Han Shie

Chun‐Wei Hsu

et al.

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2023

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Botnet‐based IoT network traffic analysis using deep learning

Singh,

Hoque,

Singh

et al. 2023

Security and Privacy

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IoT networks are increasingly being connected to a wide range of devices, and the number of devices connected has significantly increased in recent years. As a consequence, the number of vulnerabilities to IoT networks has also been increasing tremendously. In IoT networks, botnet‐based Distributed Denial of Service attack is challenging due to its dynamic behavior. The sensors and actuators connected to IoT networks are low‐powered and have less memory. Because of their inherent vulnerability, IoT devices can always be compromised by an attacker and be used to form a large botnet. A detailed analysis of IoT botnet attacks is presented in this article, along with statistics and the architectures of the botnet. We also survey the existing literature on IoT botnet traffic analysis and present a taxonomy of attack detection methods. We particularly focus on deep learning‐based methods and conduct a comparative study to evaluate their performance on IoT traffic analysis. We identify the current issues and research challenges in this field, and we conclude by highlighting some future research directions.

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Botnet‐based IoT network traffic analysis using deep learning

Singh,

Hoque,

Singh

et al. 2023

Security and Privacy

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IoT Botnet Detection Based on the Behaviors of DNS Queries

Cited by 1 publication

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Botnet‐based IoT network traffic analysis using deep learning

Botnet‐based IoT network traffic analysis using deep learning

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