Özet:

The increase in internet based devices gets security problems in cyber environment. Malwares can disturb the functioning of systems and compromise data privacy due to vulnerabilities in systems. Intrusion Detection Systems (STS) are improved to determine and classify attacks. Artificial intelligence-based methods are used more frequently to improve STS systems. In this study, literature studies using ISCX-2012 data set, which was widely used in the development of STS systems, were reviewed. Besides, by using this data set, cyber-attacks were detected with 100% accuracy with a powerful machine learning-based approach. Feature and hyperparameter selection algorithms are used to increase the classification accuracy performance of the proposed method. These machine learning approaches are thought to be useful for developing artificial intelligence-based STS systems.

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