Dr CYBER ATTACK ANALYSIS USING ARTIFICIAL NEURAL NETWORKS
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Abstract
In today's world one of the great challenges is the development of a successful and automatic cyber attack detection. This project present Artificial Intelligence techniques for cyber threat detection. The proposed methodology transforms crowd of assembled security events to individual event profiles and usage of deep learning based cyber attack recognition approach. For this aim, the event profiling of data for data preparation, pre-processing also various Artificial Neural Networks such as CNN and LSTM is developed. The benchmark dataset NSLKDD is considered for appraisal. For assessing the performance in contrast to the existing approaches, various experiments will be conducted using conventional machine learning methods (SVM, k-NN, RF, NB, and DT). Thus, the evaluation outcome of the study assure that proposed approach has potential to be operated as learning-based models for network intrusion-detection and exhibit that performance exceed the standard machine learning approaches.
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Cyber security, Network Security, Artificial Intelligence, Deep Neural Networks
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