Статьи

KIBERXAVFSIZLIK VA SUN'IY INTELLEKT: ZAMONAVIY TAHDIDLAR VA INTELLEKTUAL HIMOYA TIZIMLARI

Том 4 № 47 (2026) 74-81

2026-05-26 Статьи CC BY 4.0 Open Access

Авторы

  • Xoliqnazarov Rashidjon Farg’ona davlat texnika universiteti
  • Qo’chqorov Muhammadyahyo Farg’ona davlat texnika universiteti
  • Ergashov Shohbozbek Farg’ona davlat texnika universiteti

Аннотация

Ushbu ilmiy maqolada kiberxavfsizlik sohasida sun'iy intellekt (SI) texnologiyalarining o'rni va ahamiyati keng ko'lamda tahlil qilingan. Maqolada kibertahdidlarning zamonaviy ko'rinishlari, mashinaviy o'qitish (Machine Learning), chuqur o'qitish (Deep Learning) va neyron tarmoqlar (Neural Networks) asosida qurilgan himoya tizimlari, shuningdek, SI yordamida kiberhujumlarni aniqlash va oldini olish usullari batafsil yoritilgan. Tadqiqot davomida real hayotdagi misollar va statistik ma'lumotlarga tayanilgan holda, O'zbekiston va jahon miqyosida kiberxavfsizlik sohasidagi hozirgi holat hamda kelajakdagi rivojlanish yo'nalishlari muhokama qilingan. Maqola natijasida sun'iy intellektning kiberxavfsizlikka qo'shadigan salmoqli hissasi aniqlangan va ushbu texnologiyalarni joriy etishning strategik zarurligi asoslangan.

Ключевые слова:

kiberxavfsizlik sun'iy intellekt mashinaviy o'qitish chuqur o'qitish neyron tarmoqlar kiberhujumlar anomaliyani aniqlash tahdid razvedkasi zararli dasturlar ma'lumotlar himoyasi.

Библиографические ссылки

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Cybersecurity Ventures. (2023). Cybercrime To Cost The World 8 Trillion Annually In 2023. Cybercrime Magazine. https://cybersecurityventures.com/hackerpocalypse-cybercrime-report-2016

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NIST. (2024). Post-Quantum Cryptography Standards. National Institute of Standards and Technology. https://csrc.nist.gov/projects/post-quantum-cryptography

O'zbekiston Respublikasi Prezidentining 2022-yil 2-iyuldagi PF-128-son Farmoni. Sun'iy intellekt texnologiyalarini rivojlantirish va ularni joriy etish chora-tadbirlari to'g'risida. lex.uz

Sommer, R., & Paxson, V. (2010). Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. IEEE Symposium on Security and Privacy, 305–316.

Verizon. (2024). 2024 Data Breach Investigations Report. Verizon Communications Inc. https://www.verizon.com/business/resources/reports/dbir

Xin, Y., Kong, L., Liu, Z., et al. (2018). Machine Learning and Deep Learning Methods for Cybersecurity. IEEE Access, 6, 35365–35381. https://doi.org/10.1109/ACCESS.2018.2836950

CERT-UZ. (2023). O'zbekiston Respublikasi kompyuter hodisalariga javob berish milliy guruhi hisoboti. cert.uz

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    2026-05-26

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    Том 4 № 47 (2026)

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    Xoliqnazarov, R., Qo’chqorov, M., & Ergashov, S. (2026). KIBERXAVFSIZLIK VA SUN’IY INTELLEKT: ZAMONAVIY TAHDIDLAR VA INTELLEKTUAL HIMOYA TIZIMLARI. Наука и инновации, 4(47), 74-81. https://www.in-academy.uz/index.php/SI/article/view/50336
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