An Intrusion Detection System based on Deep Belief Networks. (arXiv:2207.02117v1 [cs.CR])

The rapid growth of connected devices has led to the proliferation of novel
cyber-security threats known as zero-day attacks. Traditional behaviour-based
IDS rely on DNN to detect these attacks. The quality of the dataset used to
train the DNN plays a critical role in the detection performance, with
underrepresented samples causing poor performances. In this paper, we develop
and evaluate the performance of DBN on detecting cyber-attacks within a network
of connected devices. The CICIDS2017 dataset was used to train …

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