Hawkware: Network Intrusion Detection Based On Behavior Analysis With Anns On An Iot Device

PROCEEDINGS OF THE 2020 57TH ACM/EDAC/IEEE DESIGN AUTOMATION CONFERENCE (DAC)(2020)

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摘要
The network-based Intrusion detection system (NIDS) plays a key role in Internet of Things (IoT) as most IoT services are network-driven. However, the existing NIDSes for IoT systems are either too costly to scale or vulnerable against advanced attacks such as traffic mimicry. In this paper, we propose a novel IDS named Hawkware, a lightweight ANN-based distributed NIDS that runs on an IoT device and analyzes the device's runtime behavior in tandem with its network traffic. By analyzing device behavior, Hawkware is able to replace expensive, deep data analysis that has traditionally been used to detect advanced attacks. Our evaluations show that Hawkware is lightweight enough to be distributed and deployed on a Raspberry PI, and yet capable of detecting such attacks at a satisfactory level.
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关键词
Internet of Things, Security, Network Intrusion Detection, Artificial Neural Networks
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