KOMPYUTER TARMOQLARIGA BO‘LADIGAN HUJUMLARNI ANIQLASH, ULARNI BARTARAF ETISH VA INTELEKTUAL DASTURNING MATEMATIK MODELINI ISHLAB CHIQISH
Ключевые слова:
Kalit so‘zi: Kompyuter tarmog‘i, axborot xavfsizligi, intelektual dastur, hujumlarni aniqlash, tarmoq hujumlari, DDoS hujumlari, MITM hujumlari, Phishing, SQL Injection, mashina o‘rganish, anomaliya aniqlash, takroriy o‘rganish (Reinforcement Learning), klasterlash (Clustering), sun’iy intelekt, tarmoq xavfsizligi, matematik model.Аннотация
Annotatsiya: Kompyuter tarmoqlariga bo‘ladigan hujumlarni aniqlash va
ularga qarshi samarali choralar ko‘rish axborot xavfsizligi sohasida dolzarb masala
hisoblanadi. Ushbu maqolada, tarmoq xavfsizligini ta’minlash maqsadida, hujumlarni
aniqlash va bartaraf etishga qaratilgan intelektual dastur uchun matematik model
ishlab chiqilgan. Model tarmoq harakatlarini real vaqtda tahlil qiladi, g‘ayritabiiy
yoki xavfli faoliyatlarni aniqlaydi va shu asosda hujumlarni avtomatik tarzda bloklash
yoki bartaraf etish choralarini ko‘radi. Matematik modelda, anomaliya aniqlash va
klasterlash algoritmlari, shuningdek, sun’iy intelekt va mashina o‘rganish
texnologiyalaridan foydalaniladi. Modelda DDoS, MITM, phishing, malware, SQL
injection kabi tarmoq hujumlari aniqlanadi va bartaraf etiladi. Modelning asosiy
afzalliklaridan biri - tizimning o‘z-o‘zini o‘rganish imkoniyatiga ega bo‘lib, yangi
turdagi hujumlarga qarshi moslashishi va tarmoq xavfsizligini yaxshilashga imkon
berishidir.
Библиографические ссылки
Foydalanilgan adabiyotlar ro‘yxati:
1. Vapnik, V. (1995). The Nature of Statistical Learning Theory. Springer.
2. Kiselev, K. A. (2019). Machine Learning in Cybersecurity: Theory, Methods,
and Applications. Springer.
3. McDonald, G. W. W. (2018). Clustering and Classification of Data: Methods
and Applications. Wiley.
4. Jain, S. (2020). Deep Learning in Cybersecurity: Applications and Challenges.
Journal of Cybersecurity and Privacy, 2020.
5. Rajput, A. S. (2019). Intrusion Detection and Prevention Systems in Computer
Networks. International Journal of Computer Science and Network Security.
6. Zhang, B. (2022). Artificial Intelligence in Cybersecurity: A Survey. Springer.
7. Chen, L. (2020). Artificial Intelligence for Network Security. IEEE Access.
8. Kotsiantis, S. S. (2007). Supervised Machine Learning: A Review of
Classification Techniques. Informatica.
9. Sharma, N., and Singh, S. (2021). Network Intrusion Detection Systems: A
Review. Journal of Computer Networks and Communications.
10. Chauhan, P. M. (2021). Advanced Intrusion Detection Systems Using Machine
Learning and Artificial Intelligence. Springer.
