Title
Gotham Testbed: A Reproducible IoT Testbed for Security Experiments and Dataset Generationxmlui.dri2xhtml.METS-1.0.item-contributorOtherinstitution
https://ror.org/03hp1m080Version
http://purl.org/coar/version/c_ab4af688f83e57aa
Rights
© 2023 IEEEAccess
http://purl.org/coar/access_right/c_abf2Publisher’s version
https://doi.org/10.1109/TDSC.2023.3247166Published at
IEEE Transactions on Dependable and Secure Computing Publisher
IEEEKeywords
Internet of Things
Botnet
Protocols
security ... [+]
Botnet
Protocols
security ... [+]
Internet of Things
Botnet
Protocols
security
malware
Servers
Sensors
emulation
machine learning
network security
testbed [-]
Botnet
Protocols
security
malware
Servers
Sensors
emulation
machine learning
network security
testbed [-]
Abstract
The growing adoption of the Internet of Things (IoT) has brought a significant increase in attacks targeting those devices. Machine learning (ML) methods have shown promising results for intrusion det ... [+]
The growing adoption of the Internet of Things (IoT) has brought a significant increase in attacks targeting those devices. Machine learning (ML) methods have shown promising results for intrusion detection; however, the scarcity of IoT datasets remains a limiting factor in developing ML-based security systems for IoT scenarios. Static datasets get outdated due to evolving IoT architectures and threat landscape; meanwhile, the testbeds used to generate them are rarely published. This paper presents the Gotham testbed, a reproducible and flexible security testbed extendable to accommodate new emulated devices, services or attackers. Gotham is used to build an IoT scenario composed of 100 emulated devices communicating via MQTT, CoAP and RTSP protocols, among others, in a topology composed of 30 switches and 10 routers. The scenario presents three threat actors, including the entire Mirai botnet lifecycle and additional red-teaming tools performing DoS, scanning, and attacks targeting IoT protocols. The testbed has many purposes, including a cyber range, testing security solutions, and capturing network and application data to generate datasets. We hope that researchers can leverage and adapt Gotham to include other devices, state-of-the-art attacks and topologies to share scenarios and datasets that reflect the current IoT settings and threat landscape. [-]
xmlui.dri2xhtml.METS-1.0.item-sponsorship
Comisión Europeaxmlui.dri2xhtml.METS-1.0.item-projectID
info:eu-repo/grantAgreement/EC/H2020/No 101021911/EU/A Cognitive Detection System for Cybersecure Operational/IDUNNCollections
- Articles - Engineering [639]
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