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DoS/DDoS-MQTT-IoT: A dataset for evaluating intrusions in IoT networks using the MQTT protocol

Authors :
Alatram, Alaa
Sikos, Leslie F.
Johnstone, Mike
Szewczyk, Patryk
Kang, James Jin
Alatram, Alaa
Sikos, Leslie F.
Johnstone, Mike
Szewczyk, Patryk
Kang, James Jin
Source :
Research outputs 2022 to 2026
Publication Year :
2023

Abstract

Adversaries may exploit a range of vulnerabilities in Internet of Things (IoT) environments. These vulnerabilities are typically exploited to carry out attacks, such as denial-of-service (DoS) attacks, either against the IoT devices themselves, or using the devices to perform the attacks. These attacks are often successful due to the nature of the protocols used in the IoT. One popular protocol used for machine-to-machine IoT communications is the Message Queueing Telemetry Protocol (MQTT). Countermeasures for attacks against MQTT include testing defenses with existing datasets. However, there is a lack of real-world test datasets in this area. For this reason, this paper introduces a DoS/DDoS-MQTT-IoT dataset—that contains various DoS/DDoS attack scenarios using MQTT traffic—to help develop and test countermeasures against such attacks. To this end, a physical IoT testbed was constructed and a large volume of IoT data was generated that included standard MQTT traffic as well as 10 DoS scenarios. The usability of the dataset has been evaluated via machine learning.

Details

Database :
OAIster
Journal :
Research outputs 2022 to 2026
Notes :
application/pdf, Research outputs 2022 to 2026
Publication Type :
Electronic Resource
Accession number :
edsoai.on1391302698
Document Type :
Electronic Resource