Remote to Local attack detection using supervised neural network
Iftikhar A. Ahmad, Azween B. Abdullah, Abdullah Sharaf Alghamdi · International Conference for Internet Technology and Secured Transactions · 2010
In order to determine Remote to Local (R2L) attack, an intrusion detection technique based on artificial neural network is presented. This technique uses sampled dataset from Kddcup99 that is standard for benchmarking of attack detection tools. The backpropagation algorithm is used for training the feedforward neural network. The developed system is applied to R2L attacks. Moreover, experiment indicates this technique has comparatively low false positive rate and false negative rate, consequently it effectively resolves the deficiency of existing intrusion detection approaches.