MASHINALI O‘QITISH ALGORITMLARI YORDAMIDA TARMOQ TRAFIKIDAGI ANOMAL HOLATLARNI ANIQLASH
Keywords:
anomaliya aniqlash, tarmoq xavfsizligi, mashinali o‘qitish, chuqur o‘rganish, gibrid model, Isolation Forest, Autoencoder, Random Forest, DDoS hujumi, normal va anomal trafik.Abstract
Ushbu maqolada kompyuter tarmoqlarida anomal holatlarni aniqlashning zamonaviy usullari va gibrid yondashuvning samaradorligi tadqiq etilgan. An’anaviy xavfsizlik tizimlarining zamonaviy kiberhujumlar (DDoS, R2L, U2R) oldidagi ojizligi tahlil qilinib, mashinali o‘rganish va chuqur o‘rganish algoritmlarining afzalliklari ko‘rsatib o‘tilgan. Tadqiqot doirasida Isolation Forest, Autoencoder va Random Forest algoritmlarini birlashtirgan gibrid model taklif etilgan. Tajriba natijalari shuni ko‘rsatadiki, taklif etilgan model 97% umumiy aniqlik (Accuracy) va 0.92 F1-score ko‘rsatkichiga ega bo‘lib, tarmoq xavfsizligini ta’minlashda yuqori ishonchlilikni namoyish etadi.
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