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Implementation of a trust-based intrusion detection system for IoT networks

Kafritsa-Georganta Sofia

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Summary

The Internet of Things (IoT) deployments are recognized as playing a pivotal role in the digital transformation era, with the potential to revolutionize all economic sectors and human activities. However, the widespread adoption of IoT solutions is impeded by significant security risks that necessitate advanced cyber defense mechanisms. Intrusion Detection Systems (IDS) are considered a crucial element of these security measures.In this thesis, a specific type of IDS that revolves around the concept of trust is investigated. Given that IoT nodes can exhibit unpredictable behavior, which can resemble malicious activity and have similar detrimental effects on the overall IoT deployment, an IDS solution based on assessing the trustworthiness of nodes is developed. This solution is deployed in a distributed manner across the IoT network, effectively monitoring the network behaviors of nodes to compute various metrics and determine whether a node exhibits acceptable behavior or shows signs of unreliability or malicious activity.These decisions are inherently dynamic and form a trust vector. Configurable thresholds enable the IDS to trigger alarms about potential offending nodes, while the computation of trust is continuously adaptive to a node’s behavior. This allows trust to be withdrawn or re-established, preventing intermittent errors from having permanent effects on the IoT network. The overall solution is designed to have low performance and memory requirements, making it suitable for all types of IoT nodes.

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