AdIoTack: Quantifying and refining resilience of decision tree ensemble inference models against adversarial volumetric attacks on IoT networks

AdIoTack: Quantifying and refining resilience of decision tree ensemble inference models against adversarial volumetric attacks on IoT networks

Machine Learning-based techniques have shown success in cyber intelligence. However, they are increasingly becoming targets of sophisticated data-driven adversarial attacks resulting in misprediction, eroding their ability to detect threats on network devices. In this paper, we present AdIoTack,1 a...

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Bibliographic Details
Main Authors: Batista, G. (Author), Habibi Gharakheili, H. (Author), Pashamokhtari, A. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2022
Subjects:
Asdversarial machine learning
Data driven
Decision trees
Ensemble models
Inference models
Internet of things
Internet protocols
Internet-of-thing network
IoT networks
Machine learning
Machine-learning
Tree ensembles
Volumetric attack
Volumetric attacks
Volumetrics
White box
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