Visualisasi Serangan Brute Force Menggunakan Metode K-Means dan Naive Bayes
Abstract
Metode K-Means dan metode Naïve Bayes diimplementasikan pada penelitian ini untuk mendapatkan hasil pengkategorian yang efektif Hasil akhir dari penelitian menunjukkan metode yang digunakan mendapatkan hasil yang baik dalam hal accuracy dengan mengurangi false alarm yang terjadi.
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D. Dede, “Most Common Attacks Affecting Today ’ s Website,”
Sucuri Blog, 2014. [Online]. Available:
https://blog.sucuri.net/2014/11/most-common-attacks-affectingtodays-websites.html. [Accessed: 20-May-2016].
M. M. Najafabadi, T. M. Khoshgoftaar, C. Kemp, N. Seliya, and R.
Zuech, “Machine learning for detecting brute force attacks at the
network level,” Proc. - IEEE 14th Int. Conf. Bioinforma. Bioeng.
BIBE 2014, pp. 379–385, 2014.
Calyptix, “Follow us ork Attack Types in 2015,” 2015. [Online].
Available: http://www.calyptix.com/top-threats/top-7-networkattack-types-in-2015-so-far/. [Accessed: 20-May-2016].
E. Haryanto, “Meningkatkan Keamanan Port SSH dengan Metode
Port Knocking Menggunakan Shorewall Pada Sistem Operasi
Linux,” Journal of Chemical Information and Modeling, vol. 53, no.
pp. 1689–1699, 2013.
V. Kumar, H. Chauhan, and D. Panwar, “K-Means Clustering
Approach to Analyze NSL-KDD Intrusion Detection Dataset,” Int. J.
Soft Comput. Eng., vol. 3, no. 4, pp. 1–4, 2013.
W. Brute and F. Report, “WordPress Brute Force Attacks,” Sucuri
Blog, 2016. [Online]. Available: https://sucuri.net/securityreports/brute-force/. [Accessed: 29-Feb-2016].
M. Kumagai, Y. Musashi, D. A. L. Roma??a, K. Takemori, S.
Kubota, and K. Sugitani, “SSH dictionary attack and DNS reverse
resolution traffic in campus network,” Proc. - 3rd Int. Conf. Intell.
Networks Intell. Syst. ICINIS 2010, pp. 645–648, 2010.
W. Yassin, N. I. Udzir, and Z. Muda, “Anomaly-Based Intrusion
Detection Through K- Means Clustering and Naives Bayes
Classification,” Proc. 4th Int. Conf. Comput. Informatics, ICOCI
, no. 49, pp. 298–303, 2013.
H. Choi, H. Lee, and H. Kim, “Fast detection and visualization of
network attacks on parallel coordinates,” Comput. Secur., vol. 28,
no. 5, pp. 276–288, 2009.
a M. Riad, I. Elhenawy, A. Hassan, and N. Awadallah, “V Isualize
N Etwork a Nomaly D Etection B Y U Sing K- Means C Lustering a
Lgorithm,” vol. 5, no. 5, pp. 195–208, 2013.
R. Zuech, T. M. Khoshgoftaar, N. Seliya, M. M. Najafabadi, and C.
Kemp, “A New Intrusion Detection Benchmarking System,” Proc.
Twenty-Eighth Int. Florida Artif. Intell. Res. Soc. Conf., no.
McHugh, pp. 252–255, 2015.
H. H. Jebur, M. A. Maarof, and A. Zainal, “Jurnal Teknologi Full
paper Identifying Generic Features of KDD Cup 1999 for Intrusion
Detection,” vol. 1, pp. 1–9, 2015.
K. S. A. Kahtani, “Improving Snort performance under Linux,” no.
April, 2009.
Y. Agusta, “K-Means - Penerapan, Permasalahan dan Metode
Terkait,” J. Sist. dan Inform., vol. 3, no. Pebruari, pp. 47–60, 2007.
A. Jananto, “Algoritma Naive Bayes untuk Mencari Perkiraan
Waktu Studi Mahasiswa P ( H | X ) P ( X | H ) P ( H ),” vol. 18, no.
, pp. 9–16, 2013.
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