Keywords
How to Cite
Abstract
Bugungi kunda kiberxavfsizlik tahdidlarining tezkor va samarali aniqlanishi tashkilotlar va tizimlar uchun muhim ahamiyat kasb etadi. Sun’iy neyron tarmoqlar (Artificial Neural Networks, ANN) ushbu tahdidlarni avtomatik ravishda aniqlashda samarali vosita sifatida keng qo‘llanilmoqda. Ushbu maqolada ANN yordamida tahdidlarni aniqlashning samaradorligi confusion matrix asosida baholandi.
References
1. Goodfellow I, Bengio Y, Courville A. Deep Learning. MIT Press; 2016.
2. Bishop CM. Pattern Recognition and Machine Learning. Springer; 2006.
3. Sommer R, Frühwirth R. Artificial neural networks in intrusion detection: A review. Computers & Security. 2016;57:1–16.
4. Dhanabal L, Shantharajah S. A study on NSL-KDD dataset for intrusion detection system based on classification algorithms. Int J Adv Res Comput Commun Eng. 2015;4(6):446–452.
5. Tavallaee M, Bagheri E, Lu W, Ghorbani AA. A detailed analysis of the KDD CUP 99 data set. IEEE Symposium on Computational Intelligence for Security and Defense Applications. 2009;1–6.
6. Kim H, Lee J. Evaluating the performance of neural networks in network intrusion detection using confusion matrix. J Inf Secur Appl. 2018;41:37–48.
7. Moustafa N, Slay J. UNSW-NB15: A comprehensive data set for network intrusion detection systems. Military Communications and Information Systems Conference (MilCIS). 2015;1–6.
This work is licensed under a Creative Commons Attribution 4.0 International License.