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Comparison of Data Mining Algorithm : PSO-KNN, PSO-RF, and PSO-DT to Measure Attack Detection Accuracy Levels on Intrusion Detection System
Sularso Budilaksono(a"), Andri Agung Riyadi(b*), Lukman Azhari (c*), Dedi Dwi Saputra (d*), M. Anno Suwarno (e*), I Gede Agus Suwartane (f*), Jupriyanto(g*), Andika Ramadhan (h*), Agus Prasetyo Utomo (i*), Achmad Fauzi (j*)

(a) Informatics Department, University of Persada Indonesia YAI
Jalan Diponegoro 74 Jakarta
*sularso2007[at]upi-yai.ac.id
(b) Magister Ilmu Komputer, STMIK Nusa Mandiri
Jalan Kramat Raya 18 Jakarta
*andriagu1603[at]nusamandiri.ac.id
(c) Teknik informatika, Universitas Muhammadiyah Tangeng
Jalan Perintis Kemerdekaan I No.1, Babakan, Kec. Tangerang, Kota Tangerang, Banten
*lukmanazhari85[at]gmail.com
(d) Pascasarjana Ilmu Komputer, STMIK Nusa Mandiri
Jalan Kramat Raya 18 Jakarta
*14002190[at]nusamandiri.ac.id
(e) Informatics Department, University of Persada Indonesia YAI
Jalan Diponegoro 74 Jakarta
*suwarno[at]upi-yai.ac.id
(f) Informatics Department, University of Persada Indonesia YAI
Jalan Diponegoro 74 Jakarta
*agus.suwartane[at]gmail.com
(g) Magister Ilmu Komputer, STMIK Nusa Mandiri
Jalan Kramat Raya 18 Jakarta
*jupriyanto.kahar[at]gmail.com
(h) Teknik informatika, Universitas Muhammadiyah Tangeng
Jalan Perintis Kemerdekaan I No.1, Babakan, Kec. Tangerang, Kota Tangerang, Banten
*andika020888[at]gmail.com
(i) Sistem Informasi, Universitas Stikubank Semarang
Jl. Trilomba Juang no 1 Semarang
*mustagus[at]edu.unisbank.ac.id
(j) Teknik informatika, Universitas Muhammadiyah Tangeng
Jalan Perintis Kemerdekaan I No.1, Babakan, Kec. Tangerang, Kota Tangerang, Banten
*ac.fauzi25[at]yahoo.com



Abstract

Nowadays computer networks are widely used to exchange important and confidential data information between servers to computer or cellular devices. Access to user control and use of software or hardware as a firewall often experience security problems. Unauthorized access to information through computer networks continues to occur and tends to increase. This study examines the attack detection mechanism by using three data mining algorithms based on particle swarm optimization (PSO), namely PSO-K Nearest Neighbor, PSO-Random Forest, and PSO-Decission Tree in the Canadian Institute for Cybersecurity Dataset (CICIDS2017). The initial experiment showed that the approach using the PSO-RF method was able to produce the highest accuracy of attack detection. Accuracy values generated using the PSO-RF algorithm with a combination of number of trees and maximal depth = 20 in the CICIDS2017 dataset are intact higher than other proposed algorithms. The highest accuracy of attack detection in the CICIDS2017 dataset is intact, which is 99.76%. In the CICIDS2017 dataset 50% Benign and 50% Attack it turns out that the PSO-RF algorithm with a combination of number of trees and maximal depth = 20 also gets the highest accuracy value of 99.67%.

Keywords: Intrusion Detection System; Particle Swarm Optimization; K-Nearest Neighbors; Random Forest; Decision Tree

Topic: International Symposium of Engineering, Technology, and Health Sciences

Link: https://ifory.id/abstract/mWtyTghKUb6q

Conference: The 3rd International Conference on Sustainability and Innovation (ICoSI 2019)

Plain Format | Corresponding Author (Sularso Budilaksono)

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