Kombinasi Metode K-Nearest Neighbor dengan Cosine Similarity untuk Prediksi Serangan Firewall pada Jaringan Komputer
Abstract
The security of the computer network, especially the internet, is very crucial to note. One of the most effective ways to secure a computer network is to use a firewall. However, making a firewall that is still manual will make it difficult for network administrators to secure their computer network. The automatic detection of attacks on the firewall will further enhance the security of the computer network. Prediction or detection of attacks on the firewall automatically and intelligently can use the K-Nearest Neighbor algorithm by measuring the distance of data similarity using Cosine Similarity. The results of this study managed to achieve a high accuracy, which is 99.71%, precision is 74.70% and recall is 74.85% of predicting traffic that goes to the firewall. The results can be used as a standard of accuracy in predicting the traffic leading to the firewall, or even create an additional firewall so that the security of computer networks, especially the user data is saved.
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DOI: http://dx.doi.org/10.32493/informatika.v6i4.12680
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