Dataset Generation Framework for Evaluation of IoT Linux Host–Based Intrusion Detection Systems

Adamczyk, Blazej; Brzeczek, Maksym; Michalak, Marcin; Kostorz, Iwona; Wawrowski, Łukasz; Hermansa, Marek; Czerwiński, Michał; Jamiolkowski, Antoni

doi:10.1109/bigdata55660.2022.10020442

Cited by 4 publications

(1 citation statement)

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“…The challenge data were generated within the simulation environment which was an extension of the software framework described in detail in [25]. This real components simulation environment consisted of an IoT device (Raspberry Pi) and additional devices responsible for HTTP traffic generating and performing the attacks.…”

Section: Fedcsis 2023 Challengementioning

confidence: 99%

Cybersecurity Threat Detection in the Behavior of IoT Devices: Analysis of Data Mining Competition Results

Czerwiński,

Michalak,

Biczyk

et al. 2023

Annals of Computer Science and Information Systems

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The paper discusses a data science competition centered around the development of an anomaly detection system for IoT devices. The competition utilized a unique environment that allowed for the operation and monitoring of real IoT devices, including scheduling of attacks on these devices. The environment was used to collect the data, which included both normal and attack-induced behavior of IoT devices. The paper presents the background of the competition, the top models submitted, and the competition results. The paper also includes a discussion about restrictions related to the use of synthetic attack data as input for constructing anomaly detection systems.

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Section: Fedcsis 2023 Challengementioning

confidence: 99%