Idetect for vulnerability detection in internet of things operating systems using machine learning

HIGHLIGHTS

SUMMARY

This section aims to provide an overview of the remaining relevant background knowledge directly related to this research, mainly machine_learning techniques used for vulnerability detection. Convolutional neural_network. Recurrent neural_network. RNNs are derived from feed-forward neural_networks and consist of layers stacked on top of each other, with neurons in each layer. Li et_al18 developed a hybrid neural_network framework of CNN and RNN for vulnerability detection in C source code. The authors built an ML system called iDetect that deploys a trained RF model to detect the vulnerabilities that exist in the C/C++ source . . .

 



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