UTAS Conferences
type: channel
description: This journal, called UTAS Conferences, was founded in 2026. The founder of this journal is the University of Tashkent for Applied Sciences (UTAS). This journal serves to index all local and international conferences organized by the University of Tashkent for Applied Sciences in international databases. For several years now, the University of Tashkent for Applied Sciences, together with its partners and various organizations, has been organizing several scientific and practical conferences throughout the year. It is planned to place several hundred abstracts received at such conferences on this site, obtain a DOI number for each article, and index them in several international databases.
publisher: University of Tashkent for Applied Sciences
language: en
publication name: UTAS Conferences
items: NUTQIY KO‘NIKMALARNI RIVOJLANTIRISHDA O‘LKASHUNOSLIK MATERIALLARI USTIDA ISHLASHDA AUTENTIK MATERIALLARDAN FOYDALANISH
items: SOLIQ NAZORATINI TASHKIL ETISHDA XALQARO TAJRIBA IMKONIYATLARINI AMALIYOTDA TAKOMILLASHTIRISH
items: DARKNET VA GLOBAL KIBERJINOYATCHILIK EVOLYUTSIYASI
items: DEEPFAKE TEXNOLOGIYALARINING KIBERXAVFSIZLIKKA TAHDIDI
items: SUN’IY INTELLEKT YORDAMIDA YOLG‘ON AXBOROT TARQATISH MEXANIZMLARI
items: КИБЕРХАВФСИЗЛИКНИ ТАЪМИНЛАШ МАСАЛАЛАРИДА СУНЪИЙ ИНТЕЛЛЕКТ ИМКОНИЯТЛАРИ
items: OPERATSION TIZIMLARDA XAVFSIZLIK SIYOSATLARI VA MODELLARI
items: SUN’IY INTELLEKT USULLАRI АSOSIDА ELEKTRON RАQАMLI IMZO АLGORITMLАRINING KRIPTOGRАFIK TАHLILI
items: KIBERXAVFSIZLIK VA SUNIY INTELLEKT INTEGRATSIYASI
items: USER BEHAVIOR ANALYTICS FOR DETECTING AI-DRIVEN SOCIAL ENGINEERING ATTACKS
items: GENERATIV SUNʼIY INTELLEKTDAGI TAʼLIM TIZIMLARINING TRANSFORMACIYASI VA KIBERXAVFSIZLIK: NEYRON TARMOQLAR YORDAMIDA AES VA RSA KRIPTOANALIZI
items: SUN’IY INTELLEKT YORDAMIDA AVTOMATLASHTIRILGAN TEST VA BAHOLASH TIZIMI
items: GENERATIV SUN’IY INTELLEKT YORDAMIDAGI KIBERXAVFSIZLIK TAHDIDLARINI ANIQLASHDA GIBRID ONTOLOGIK-GENERATIV MODEL (HOG-M)
items: GENERATIV SUN’IY INTELLEKT ILOVALARIDA KIBERXAVFSIZLIK: PROMPT INJECTION VA MA’LUMOTLARNI ZAHARLASH TAHDIDLARI HAMDA HIMOYA USULLARI
items: KIBERXAVFSIZLIKNI AVTOMATLASHTIRISHDA SUN’IY INTELLEKT ROLI
items: DEEP LEARNING FOR IOT INTRUSION DETECTION SYSTEMS: ANALYTICAL STUDY
items: DEFENSE AND RESILIENCE OF AI SYSTEMS FOR OPTIMIZING CRYPTANALYSIS IN DEFENSE APPLICATIONS: DEVELOPING ROBUST CIPHERS THROUGH MACHINE LEARNING AND PREEMPTIVE WEAKNESS DETECTION
items: MESSENJERLARDA TARQALADIGAN PHISHING, MALWARE VA SCAM TAHDIDLARINI REAL VAQT REJIMIDA ANIQLASH VA TAHLIL QILISH TIZIMLARI
items: DETECTING ATTACKS ON MOBILE PLATFORMS USING ARTIFICIAL INTELLIGENCE: A CYBER BROTHER APPROACH
items: KIBERXAVFSIZLIKDA INSON OMILI VA SI INTEGRATSIYASI
items: KIBERXAVFSIZLIKDA INTELLEKTUAL TEXNOLOGIYALAR ROLI: SUN’IY INTELEKT VA ILG‘OR HIMOYA MEXANIZMLARI
items: AQLLI KIBERHIMOYA: MOBIL EKOTIZIMLARDA OFLAYN AI MODELLARINING SAMARADORLIGI
items: SUN’IY INTELLEKTGA ASOSLANGAN IDS (HUJUMNI ANIQLASH TIZIMLARI) ORQALI KIBERHUJUMLARNI BARVAQT PROGNOZLASH
items: IMPROVING LEGAL MECHANISMS FOR DETECTING CYBERCRIMES BASED ON STATISTICAL ANALYSIS OF FINANCIAL TRANSACTIONS IN THE BANKING SYSTEM
items: ARTIFICIAL INTELLIGENCE AND CYBERSECURITY IN MODERN INFORMATION TECHNOLOGY EDUCATION
items: DEEPFAKE TEXNOLOGIYASINING KIBERXAVFSIZLIK TIZIMLARIGA TA’SIRI
items: KORXONA AXBOROT TIZIMLARIDA MA’LUMOTLAR ZAXIRA NUSXALARINING XAVFSIZLIGINI TA’MINLASHDA TAHDIDLAR VA ULARGA QARSHI ZAMONAVIY YECHIMLAR
items: GENERATIV SUN’IY INTELLEKT SHAROITIDA WEB-SESSIYA TOKENLARI XAVFSIZLIGINI TA’MINLASH, TAHDIDLAR VA HIMOYA MEXANIZMLARI
items: AI ASOSIDAGI SIMULYATSIYALAR YORDAMIDA KIBERXAVFSIZLIKNI O‘QITISH: ETHICAL HACKING YONDASHUVINING SAMARADORLIGI VA XAVFSIZLIK MUAMMOLARI

NUTQIY KO‘NIKMALARNI RIVOJLANTIRISHDA O‘LKASHUNOSLIK MATERIALLARI USTIDA ISHLASHDA AUTENTIK MATERIALLARDAN FOYDALANISH
type: item
description: Ingliz tili nafaqat xalqaro muloqot vositasi, balki ilmiy-texnik taraqqiyot, ta'lim va kasbiy rivojlanishning muhim omiliga aylangan. Shu boisdan, ingliz tili o‘qitish metodikasini takomillashtirish, ayniqsa, tinglab tushunish ko‘nikmasini rivojlantirishga qaratilgan tadqiqotlar dolzarb masalalardan biri bo‘lib qolmoqda.
subject: Articles
  topic: section
subject: autentik manbalar
  topic: keywords
subject: kommunikativ topshiriqlar
  topic: keywords
subject: kompleks pedagogik tizim
  topic: keywords
creator: Saitxanova Dinara
rights: Copyright (c) 2026
date: 2026-01-15
publication date: 2026-01-15
starting page: 1939
ending page: 1942
doi: 10.65164/0vs8ej14

SOLIQ NAZORATINI TASHKIL ETISHDA XALQARO TAJRIBA IMKONIYATLARINI AMALIYOTDA TAKOMILLASHTIRISH
type: item
description: Soliq nazoratini tashkil etish va soliq qarzdorligini undirishning samarali mexanizmlari, shuningdek xalqaro tajribalarni O‘zbekiston sharoitida tatbiq etish imkoniyatlarini tahlil qiladi. Maqolada AQSh, Buyuk Britaniya va Yaponiya soliq tizimidagi ilg‘or amaliyotlar o‘rganilgan bo‘lib, soliq qarzdorligini kamaytirish va soliq tushumlarini oshirishga xizmat qiluvchi mexanizmlar batafsil yoritilgan. Xususan, maqolada raqamli soliq platformalari, risk asosida soliq auditi, soliqlarni to‘lashda rag‘batlantirish tizimlari va xalqaro ma’lumot almashinuvi kabi zamonaviy yondashuvlar tahlil qilingan. Shu bilan birga, har bir davlat tajribasining O‘zbekiston sharoitida tatbiq etish yo‘nalishlari va samaradorlik imkoniyatlari keltirilgan. Maqola soliq ma’muriyatchiligini takomillashtirish, soliq to‘lovchilarning mas’uliyatini oshirish va raqamli texnologiyalar orqali soliq tizimining samaradorligini kuchaytirish bo‘yicha ilmiy-amaliy tavsiyalarni taqdim etadi. Ushbu tadqiqot O‘zbekiston soliq tizimida islohotlar olib borish, soliq qarzdorligini kamaytirish va davlat budjeti tushumlarini barqaror oshirishga qaratilgan siyosatni shakllantirish uchun asos bo‘lib xizmat qilishi mumkin.Kalit soʻzlar: soliq tizimi, soliq to‘lovchi, soliq nazorati, soliq tushumlari, xalqaro tajriba, shikoyat, davlat, budjet.
subject: Articles
  topic: section
subject: tax system, taxpayer, tax control, tax revenues, international experience, complaint, state, budget
  topic: keywords
creator: Nizomxonov Elbekxon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 1793
ending page: 1797
doi: 10.65164/hj1fa129

DARKNET VA GLOBAL KIBERJINOYATCHILIK EVOLYUTSIYASI
type: item
description: Raqamli texnologiyalar rivojlanishi bilan bir qatorda internetning yashirin qatlamlari ham shakllanib bordi. Ular orasida Darknet alohida o‘rin egallaydi. Darknet — bu oddiy qidiruv tizimlari orqali topib bo‘lmaydigan, maxsus dasturiy vositalar yordamida kiriladigan tarmoq segmenti bo‘lib, u anonimlikni ta’minlashga qaratilgan texnologiyalar asosida ishlaydi. Ushbu muhitning asosiy xususiyati foydalanuvchilarning shaxsini yashirish va ularning faoliyatini kuzatishni murakkablashtirishdir.
subject: Articles
  topic: section
creator: Ruzibayev Eldorjon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 620
ending page: 624
doi: 10.65164/65ff3z80

DEEPFAKE TEXNOLOGIYALARINING KIBERXAVFSIZLIKKA TAHDIDI
type: item
description: XXI asr axborot texnologiyalarining keskin rivojlanishi bilan tavsiflanadigan murakkab davr sifatida namoyon bo‘lmoqda. Raqamli texnologiyalar insoniyat hayotining deyarli barcha sohalariga chuqur kirib borgani sari axborot almashinuvi tezligi ortib, virtual makon global kommunikatsiya maydoniga aylandi. Ayniqsa, sun’iy intellekt texnologiyalarining rivojlanishi multimedia mahsulotlarini yaratish jarayonini mutlaqo yangi bosqichga olib chiqdi. Biroq texnologik taraqqiyot bilan bir qatorda kiberxavfsizlikka oid yangi tahdidlar ham yuzaga kelmoqda. Ana shunday xavfli va murakkab texnologiyalardan biri deepfake texnologiyasi hisoblanadi.
subject: Articles
  topic: section
creator: Sh.Sh.Yuldasheva
creator: Ruzibayev Eldorjon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 614
ending page: 619
doi: 10.65164/9wtd9v38

SUN’IY INTELLEKT YORDAMIDA YOLG‘ON AXBOROT TARQATISH MEXANIZMLARI
type: item
description: Ushbu maqolada sun’iy intellekt texnologiyalaridan foydalanib yolg‘on axborotlarni yaratish va tarqatish mexanizmlari tahlil qilinadi. Jumladan, neyrotarmoqlar, deepfake texnologiyalari, avtomatlashtirilgan bot tizimlari hamda matn generatsiya qiluvchi dasturlar orqali noto‘g‘ri ma’lumotlarni ommaga tezkor yetkazish usullari yoritilgan. Shuningdek, bunday axborotlarning jamiyat, siyosat va axborot xavfsizligiga salbiy ta’siri ko‘rib chiqiladi. Maqolada yolg‘on axborotlarni aniqlash va ularga qarshi kurashishning zamonaviy usullari hamda media savodxonlikning ahamiyati haqida fikr yuritiladi.
subject: Articles
  topic: section
subject: generative, sun’iy intellekt,modellar, generativ adversarial
  topic: keywords
creator: Sharopova Muxayyo
creator: Ruzibayev Eldorjon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 607
ending page: 613
doi: 10.65164/jadpd669

КИБЕРХАВФСИЗЛИКНИ ТАЪМИНЛАШ МАСАЛАЛАРИДА СУНЪИЙ ИНТЕЛЛЕКТ ИМКОНИЯТЛАРИ
type: item
description: Мазкур мақолада сунъий интеллектнинг киберхавфсизликни таъминлаш масалаларидаги роли ва имкониятлари ўрганилади. Кибермакондаги таҳдидларнинг кўплиги ва мураккаблиги анъанавий ҳимоя чоралари билан курашишни мураккаблаштираётгани таъкидланади. Мақолада кибрхавфсизлик соҳасидаги баъзи муаммолар таҳлили, сунъий интеллект имкониятлари, амалий ечимлар ва таклифлар ҳамда хулосалар келтирилган.
subject: Articles
  topic: section
subject: киберхавфсизлик, сунъий интеллект, киберҳужумлар, аномалия аниқлаш, хавфсизлик технологиялари.
  topic: keywords
creator: Айсаев Искандар
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 603
ending page: 606
doi: 10.65164/4n3wa521

OPERATSION TIZIMLARDA XAVFSIZLIK SIYOSATLARI VA MODELLARI
type: item
description: Ushbu maqolada operatsion tizimlarda xavfsizlik siyosatlari va modellari tahlil qilinadi. Axborot xavfsizligini ta’minlashda qo‘llaniladigan asosiy yondashuvlar, jumladan, Bell-LaPadula va Biba xavfsizlik modellari ko‘rib chiqiladi. Shuningdek, foydalanuvchi huquqlarini boshqarish, tizim resurslarini himoyalash hamda ma’lumotlarning maxfiyligi, yaxlitligi va mavjudligini ta’minlash masalalari yoritilgan.
subject: Articles
  topic: section
subject: Operatsion tizim, xavfsizlik siyosati, xavfsizlik modeli, Bell-LaPadula, Biba, autentifikatsiya, avtorizatsiya, maxfiylik, yaxlitlik, mavjudlik
  topic: keywords
creator: Allaberganova Nasiba
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 597
ending page: 602
doi: 10.65164/686vn423

SUN’IY INTELLEKT USULLАRI АSOSIDА ELEKTRON RАQАMLI IMZO АLGORITMLАRINING KRIPTOGRАFIK TАHLILI
type: item
description: Mаzkur mаqolаdа DSА vа ECDSА elektron rаqаmli imzo аlgoritmlаrining mаtemаtik аsoslаri, ishlаsh prinsiplаri hаmdа ulаrning o‘zаro o‘xshаsh vа fаrqli jihаtlаri tаhlil qilinаdi. Аlgoritmlаrning kriptogrаfik bаrdoshliligi, kаlit uzunligi vа hisoblаsh sаmаrаdorligi nuqtаi nаzаridаn solishtirilаdi. Shuningdek, ECDSА аlgoritmidа tаsodifiy pаrаmetr k ning tаkrorаn ishlаtilishi nаtijаsidа yuzаgа kelаdigаn xаvfsizlik muаmmosi mаtemаtik jihаtdаn ko‘rib chiqilаdi.
subject: Articles
  topic: section
subject: DSА, ECDSА, elektron rаqаmli imzo, sun’iy intellekt, mаshinаviy o‘rgаnish, kriptogrаfiyа, аnomаliyаlаrni аniqlаsh, Big dаtа
  topic: keywords
creator: Urozovа Sevinch
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 591
ending page: 596
doi: 10.65164/fh46sw37

KIBERXAVFSIZLIK VA SUNIY INTELLEKT INTEGRATSIYASI
type: item
description: Ushbu maqolada kiberxavfsizlikni ta’minlashda sun’iy intellekt (SI) texnologiyalarini integratsiya qilish masalalari tadqiq etiladi. Zamonaviy kiberhujumlarning murakkablashishi sharoitida mashinali o‘rganish va chuqur o‘rganish algoritmlarining tahdidlarni aniqlash va ularga qarshi harakat qilishdagi samaradorligi tahlil qilingan. Shuningdek, maqolada SI tizimlaridan ham himoya, ham hujum vositasi sifatida foydalanishning ikki yoqlama xususiyati va kelajakdagi xavfsizlik arxitekturasini yaratish istiqbollari yoritilgan.
subject: Articles
  topic: section
subject: kiberxavfsizlik, sun’iy intellekt, mashinali o‘rganish, anomaliyalarni aniqlash, kiberhujum, ma’lumotlar himoyasi.
  topic: keywords
creator: Xaqqulova Ra’no
creator: Atajonov Umidjon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 586
ending page: 590
doi: 10.65164/mds6jc53

USER BEHAVIOR ANALYTICS FOR DETECTING AI-DRIVEN SOCIAL ENGINEERING ATTACKS
type: item
description: Social engineering remains a persistent security problem because it exploits human decision-making instead of only software flaws. Recent evidence shows that identity misuse and human-driven mistakes continue to be major breach pathways: Verizon's 2025 Data Breach Investigations Report analyzed more than 22,000 incidents and 12,195 confirmed breaches, while credential abuse remained a leading initial attack vector at 22% [1]. This paper examines how behavioral security analytics, user and entity behavior analytics (UEBA), deep learning, deep evidential clustering (DEC), explainable AI (XAI), and federated learning (FL) can defend against social engineering and insider threats. This work synthesizes published results and compares methods, datasets, formulas, advantages, limitations, and deployment gaps. The review finds that AI-driven behavioral analytics can reduce false positives, detect subtle post-login behavior changes, and provide analyst explanations; however, real-world deployment is limited by dataset imbalance, privacy constraints, cold-start baselines, model poisoning, and the difficulty of inferring human intent from logs alone. The paper concludes that the strongest defense is not fully automated surveillance, but a human-centered system that combines contextual behavior modeling, privacy-preserving learning, explainable alerts, and continuous security awareness.
subject: Articles
  topic: section
subject: social engineering, behavioral analytics, UEBA, insider threat detection, deep evidential clustering, federated learning, explainable AI, cybersecurity.
  topic: keywords
creator: Nurmukhammad Nuriddinov
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 577
ending page: 585
doi: 10.65164/41y5qr89

GENERATIV SUNʼIY INTELLEKTDAGI TAʼLIM TIZIMLARINING TRANSFORMACIYASI VA KIBERXAVFSIZLIK: NEYRON TARMOQLAR YORDAMIDA AES VA RSA KRIPTOANALIZI
type: item
description: Ushbu ilmiy maqolada generativ sunʼiy intellekt (GSI) vositalarining kriptoanaliz sohasidagi yangi xavflari tahlil qilinadi. 2026 yilga kelib, ChatGPT-4o va Sber GigaChat 3.0 kabi modellar kriptografik tizimlarga hujum qilish imkoniyatlarini sezilarli darajada kengaytirdi. Xususan, neyron tarmoqlar asosida AES-128 va RSA-1024 algoritmlariga qarshi samarali hujum arxitekturalari ishlab chiqildi. Maqolada CNN va LSTM arxitekturalari yordamida S-Box modellash, differensial diffuziya va side-channel hujumlar (vaqt va quvvat tahlili) orqali kalitlarni tiklash usullari keltirilgan. Taklif etilgan neyron AES cracker modeli klassik toʻliq qidiruvga nisbatan 23 marta tezlikka erishadi (xavfsizlik darajasi 292 ga tushadi). RSA-1024 faktorizatsiyasi LSTM va vaqtli side-channel maʼlumotlari asosida 4.1 marta tezlashadi. Haqiqiy hujum misollari IoT qurilmalari, VPN tarmoqlari va Telegramning eski kriptografik protokollariga qaratilgan. Natijalar GSI rivojlanishi kriptografik himoyani tubdan qayta koʻrib chiqish zarurligini koʻrsatadi.
subject: Articles
  topic: section
subject: generativ AI kriptoanalizi, neyron tarmoq hujumlari, AES-128 S-Box modellash, RSA faktorizatsiyasi, side-channel quvvat tahlili, diffuziya modellari, GPT-4o xavflari, xavfsiz AI arxitekturalari
  topic: keywords
creator: Andrey Dragunov
creator: Anna Tomskova
creator: Askarova Ayjamal
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 572
ending page: 576
doi: 10.65164/p990jv06

SUN’IY INTELLEKT YORDAMIDA AVTOMATLASHTIRILGAN TEST VA BAHOLASH TIZIMI
type: item
description: Ushbu maqolada ta’lim tizimida sun’iy intellekt asosida avtomatlashtirilgan test va baholash tizimlarini yaratishning nazariy va amaliy jihatlari yoritilgan. Talabalar bilimini baholash jarayonini optimallashtirish, inson omilini kamaytirish va baholash aniqligini oshirish masalalari ko‘rib chiqilgan. Shuningdek, mashina o‘qitish va tabiiy tilni qayta ishlash texnologiyalaridan foydalanish orqali test tizimlarini takomillashtirish imkoniyatlari tahlil etilgan. Maqolada avtomatlashtirilgan test tizimining ishlash algoritmi, JSON formatidagi savollar bazasi hamda foydalanuvchi interfeysi tavsiflangan. Natijada, ushbu tizim ta’lim sifatini oshirish va o‘qitish jarayonini individuallashtirishga xizmat qilishi asoslab berilgan.
subject: Articles
  topic: section
subject: sun’iy intellekt, avtomatlashtirilgan test tizimi, baholash, mashina o‘qitish, NLP, ta’lim texnologiyalari, adaptiv o‘qitish, JSON, elektron ta’lim
  topic: keywords
creator: Sadikova Shaxnoza
creator: Azimova Umida
creator: Sadikova Feruzaxon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 567
ending page: 571
doi: 10.65164/3r2xjq87

GENERATIV SUN’IY INTELLEKT YORDAMIDAGI KIBERXAVFSIZLIK TAHDIDLARINI ANIQLASHDA GIBRID ONTOLOGIK-GENERATIV MODEL (HOG-M)
type: item
description: Ushbu tezisda generativ sun'iy intellekt (GenAI) texnologiyalarining kiberxavfsizlik sohasida yaratgan yangi avlod tahdidlari — deepfake phishing, LLM-asosidagi ijtimoiy muhandislik, prompt injection va gallyutsinatsiya-asosidagi dezinformatsiya — tizimli tahlil qilinadi. An'anaviy IDS va klassik RAG tizimlarining bu tahdidlarni yetarli aniqlikda aniqlashga qodir emasligi ko'rsatiladi. Muallif tomonidan ishlab chiqilayotgan HOG-M (Hybrid Ontological-Generative Model) tizimi UCO va MITRE ATT&CK ontologiyasi, FAISS vektorli qidiruv va RRF gibrid birlashtirish algoritmiga asoslanib, GenAI-tahdidlarni F1=0.92 aniqlikda, gallyutsinatsiya darajasini esa 5.7% gacha kamaytirib aniqlash imkonini beradi. 500 ta tahdid hodisasi ustida o'tkazilgan eksperiment natijalari jadvallar va grafiklar ko'rinishida taqdim etiladi.
subject: Articles
  topic: section
subject: generativ sun'iy intellekt, kiberxavfsizlik, deepfake, prompt injection, HOG-M, MITRE ATT&CK, ontologiya, gallyutsinatsiya, RAG, xavfsiz AI arxitekturasi, IDS.
  topic: keywords
creator: Absalamova Diyora
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 563
ending page: 566
doi: 10.65164/nqxdwh23

GENERATIV SUN’IY INTELLEKT ILOVALARIDA KIBERXAVFSIZLIK: PROMPT INJECTION VA MA’LUMOTLARNI ZAHARLASH TAHDIDLARI HAMDA HIMOYA USULLARI
type: item
description: Ushbu maqolada generativ sunʻiy intellekt (SI) ilovalarida uchrashuvchi eng dolzarb kiberxavfsizlik tahdidlari — prompt injection (koʻrsatmani almashtirish hujumi) va data poisoning (maʻlumotlarni zaharlash) — tizimli adabiyotlar sharhi (systematic literature review) usuli orqali tahlil qilinadi. Google Scholar, arXiv, IEEE Xplore va OWASP bazalaridan 2022–2025-yillar oraliğida chop etilgan 10 ta birlamchi manba tanlab oʿrganildi. Maqolada hujum mexanizmlari, ularning real tizimlarga taʻsiri, mavjud himoya usullarining samaradorligi va Oʻzbekiston sharoitiga xos xavf omillari koʻrib chiqiladi. Natijalar shuni koʻrsatadiki, prompt injection va data poisoning hozircha ochiq muammo boʻlib qolmoqda va red-teaming hamda runtime sandboxing (ish vaqtida izolyatsiya) ni birlashtirgan gibrid himoya yondashuvlarini talab etmoqda. Maqola Oʻzbekistonda generativ SI ilovalarini ishlab chiquvchi mutaxassislar va tadqiqotchilar uchun amaliy ahamiyat kasb etadi.
subject: Articles
  topic: section
subject: generativ sunʻiy intellekt, kiberxavfsizlik, prompt injection, data poisoning, LLM, xavfsiz arxitektura, backdoor hujumlari, tizimli adabiyotlar sharhi.
  topic: keywords
creator: Oʻralov Rustamjon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 558
ending page: 562
doi: 10.65164/z0p1a738

KIBERXAVFSIZLIKNI AVTOMATLASHTIRISHDA SUN’IY INTELLEKT ROLI
type: item
description: Ushbu maqolada kiberxavfsizlikni avtomatlashtirish jarayonida Sun’iy intellekt texnologiyalarining o‘rni keng va chuqur yoritilgan. Zamonaviy axborot tizimlarida xavfsizlikni ta’minlashda avtomatlashtirilgan yondashuvlarning ahamiyati, tahdidlarni aniqlash, tahlil qilish va ularga tezkor javob berishda Machine Learning algoritmlarining roli batafsil tahlil qilingan. Shuningdek, Security Operations Center faoliyatida sun’iy intellektdan foydalanishning amaliy jihatlari, afzalliklari, muammolari va istiqbollari keng ko‘rib chiqilgan.
subject: Articles
  topic: section
subject: kiberxavfsizlik, sun’iy intellekt, mashinaviy o‘rganish, avtomatlashtirish, tahdidlarni aniqlash, SOC, axborot xavfsizligi, raqamli himoya, kiberhujumlar, anomaliya tahlili
  topic: keywords
creator: Botirova Nigoraxon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 555
ending page: 557
doi: 10.65164/hm073g19

DEEP LEARNING FOR IOT INTRUSION DETECTION SYSTEMS: ANALYTICAL STUDY
type: item
description: The exponential spreading of Internet of Things (IoT) devices has dramatically expanded the attack surface of modern networks, rendering traditional intrusion detection systems (IDS) inadequate against increasingly sophisticated cyber threats. This paper presents a comprehensive comparative study of state-of-the-art deep learning (DL)-based IDS approaches for IoT security, examining Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), hybrid CNN-LSTM architectures, Deep Neural Networks (DNN), Autoencoders (AE), and Federated Learning (FL)-based frameworks. We systematically evaluate these approaches across five widely adopted benchmark datasets: NSL-KDD, UNSW-NB15, BoT-IoT, TON-IoT, and CICIoT2023 and assess their performance in terms of accuracy, precision, recall, F1-score, and computational overhead. Two real-world case studies, one of them is 2016 Mirai Botnet attack on Dyn DNS infrastructure and the 2021 Oldsmar water treatment plant intrusion are employed to illustrate the practical limitations of conventional security approaches and to demonstrate how AI-driven IDS could have mitigated these incidents. Our analysis reveals that hybrid CNN-LSTM models consistently achieve detection rates exceeding 99\% while maintaining low false positive rates, but significant trade-offs exist between detection accuracy and resource efficiency for edge-deployed IoT environments. We further identify critical open challenges including class imbalance, concept drift, adversarial robustness, and dataset obsolescence and propose future research directions centred on lightweight models, federated learning, and transfer learning for real-world IoT deployments.
subject: Articles
  topic: section
subject: Internet of Things, Intrusion Detection Systems, Deep Learning, CNN, LSTM, Federated Learning,Cybersecurity, Anomaly Detection,Botnet, ICS Security
  topic: keywords
creator: Shaxzod Mirmuminov
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 543
ending page: 554
doi: 10.65164/bwr26y63

DEEP LEARNING FOR IOT INTRUSION DETECTION SYSTEMS: ANALYTICAL STUDY
type: item
description: The exponential spreading of Internet of Things (IoT) devices has dramatically expanded the attack surface of modern networks, rendering traditional intrusion detection systems (IDS) inadequate against increasingly sophisticated cyber threats. This paper presents a comprehensive comparative study of state-of-the-art deep learning (DL)-based IDS approaches for IoT security, examining Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), hybrid CNN-LSTM architectures, Deep Neural Networks (DNN), Autoencoders (AE), and Federated Learning (FL)-based frameworks. We systematically evaluate these approaches across five widely adopted benchmark datasets: NSL-KDD, UNSW-NB15, BoT-IoT, TON-IoT, and CICIoT2023 and assess their performance in terms of accuracy, precision, recall, F1-score, and computational overhead. Two real-world case studies, one of them is 2016 Mirai Botnet attack on Dyn DNS infrastructure and the 2021 Oldsmar water treatment plant intrusion are employed to illustrate the practical limitations of conventional security approaches and to demonstrate how AI-driven IDS could have mitigated these incidents. Our analysis reveals that hybrid CNN-LSTM models consistently achieve detection rates exceeding 99\% while maintaining low false positive rates, but significant trade-offs exist between detection accuracy and resource efficiency for edge-deployed IoT environments. We further identify critical open challenges including class imbalance, concept drift, adversarial robustness, and dataset obsolescence and propose future research directions centred on lightweight models, federated learning, and transfer learning for real-world IoT deployments.
subject: Articles
  topic: section
subject: Internet of Things, Intrusion Detection Systems, Deep Learning, CNN, LSTM, Federated Learning,Cybersecurity, Anomaly Detection,Botnet, ICS Security
  topic: keywords
creator: Shaxzod Mirmuminov
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 543
ending page: 554
doi: 10.65164/mpkggp49

DEFENSE AND RESILIENCE OF AI SYSTEMS FOR OPTIMIZING CRYPTANALYSIS IN DEFENSE APPLICATIONS: DEVELOPING ROBUST CIPHERS THROUGH MACHINE LEARNING AND PREEMPTIVE WEAKNESS DETECTION
type: item
description: The rapid advancement of generative AI models in 2026, including GPT-4o and LLaMA 3.1, has demonstrated unprecedented capabilities in automated cryptanalysis. These models can break classical ciphers such as Vigenère 15.7 times faster than brute-force methods, posing immediate threats to defense communication systems. This paper introduces CryptoDefender, a novel adversarial training architecture that synthesizes robust block ciphers with preemptive weakness detection. Unlike traditional approaches that evaluate ciphers after design, CryptoDefender integrates a CipherGAN attack simulator during the training phase, forcing the cipher generator to evolve against adaptive neural cryptanalysis. The methodology achieves a 2.2x security margin improvement over GOST R 34.12-2015 baseline and resists 95% of AI-based cryptanalysis attacks in controlled experiments. Empirical validation includes legacy VPN protocols and IoT edge devices, demonstrating practical deployability. The paper provides pseudocode, hyperparameter configurations, and comparative resilience curves. CryptoDefender represents the first generative AI-resistant cipher synthesis framework suitable for government and military applications requiring long-term confidentiality against adaptive adversaries.
subject: Articles
  topic: section
subject: Generative AI cryptanalysis; robust ciphers; adversarial training; CipherGAN; CryptoDefender; GOST R 34.12-2015; defense applications; preemptive weakness detection
  topic: keywords
creator: A. Dragunov
creator: A. Askarova
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 537
ending page: 542
doi: 10.65164/1kj5k331

MESSENJERLARDA TARQALADIGAN PHISHING, MALWARE VA SCAM TAHDIDLARINI REAL VAQT REJIMIDA ANIQLASH VA TAHLIL QILISH TIZIMLARI
type: item
description: Ushbu maqolada messenjer ilovalarida tarqaladigan fishing, zararli dasturlar (malware) va firibgarlik (scam) tahdidlarini real vaqt rejimida aniqlash va tahlil qilish tizimlarini ishlab chiqishning metodologik va amaliy jihatlarini koʻrib chiqadi. Tadqiqotda sun’iy intellekt va mashina oʻqitish (AI/ML) usullari, tabiiy tilni qayta ishlash (NLP) algoritmlari, xatti-harakatlar tahlili va kriptografik imzolarni tekshirish texnologiyalari integratsiyalashgan arxitektura taklif qilinadi. Natijalar shuni koʻrsatadiki, taklif etilayotgan tizim 94,2% aniqlik bilan tahdidlarni aniqlashga qodir boʻlib, real vaqt rejimida 50 ms dan kam kechikish bilan ishlaydi. Ushbu natijalar messenjer xavfsizligini oshirish va foydalanuvchi ma’lumotlarini himoya qilishda muhim ahamiyatga ega.
subject: Articles
  topic: section
subject: Messenjer xavfsizligi, real vaqt rejimida aniqlash, fishing, zararli dastur, firibgarlik, sun’iy intellekt, mashina oʻqitish, NLP, xavfsizlik tahlili.
  topic: keywords
creator: Eshchanov Shamsiddin
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 532
ending page: 536
doi: 10.65164/c46zg654

DETECTING ATTACKS ON MOBILE PLATFORMS USING ARTIFICIAL INTELLIGENCE: A CYBER BROTHER APPROACH
type: item
description: The rapid expansion of mobile ecosystems has significantly increased the attack surface for cyber threats. This paper explores the application of Artificial Intelligence (AI) techniques in detecting and mitigating cyberattacks on mobile platforms. As a case study, the Cyber Brother mobile security system is analyzed, focusing on its ability to detect malicious APK files and phishing URLs in real time. The system utilizes on-device machine learning models to ensure privacy-preserving and offline threat detection. Experimental observations indicate that AI-driven approaches outperform traditional signature-based methods, especially in identifying zero-day attacks. The study highlights the effectiveness, limitations, and future potential of AI-based mobile cybersecurity solutions.
subject: Articles
  topic: section
subject: Artificial Intelligence, Mobile Security, Cybersecurity, APK Analysis, URL Detection, Malware, On-device AI, Cyber Brother
  topic: keywords
creator: Abbaz Primbetov
creator: Xusniddin Xamidov, Kamron Mamedov, Muhammadillo Xakimov
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 527
ending page: 531
doi: 10.65164/cz438417

KIBERXAVFSIZLIKDA INSON OMILI VA SI INTEGRATSIYASI
type: item
description: Mazkur maqolada kiberxavfsizlik tizimlarida inson omilining roli va uning sun’iy intellekt (SI) texnologiyalari bilan integratsiyasi chuqur ilmiy tahlil qilinadi. Tadqiqotlar shuni ko‘rsatadiki, global kiberhodisalarning qariyb 74–82% i inson xatolari (phishing, ijtimoiy muhandislik, noto‘g‘ri konfiguratsiya) bilan bog‘liq. Shu bilan birga, SI asosidagi xavfsizlik tizimlari tahdidlarni aniqlash tezligini 60–90% gacha oshirishi va noto‘g‘ri pozitiv natijalarni 30–40% ga kamaytirishi aniqlangan. Maqolada insonning kognitiv zaifliklari, qaror qabul qilishdagi cheklovlari hamda SI algoritmlarining adaptiv o‘rganish imkoniyatlari o‘zaro uyg‘unlikda ko‘rib chiqiladi. Natijada, “inson + SI” gibrid modeli zamonaviy kiberxavfsizlikning eng samarali strategiyasi sifatida asoslanadi.
subject: Articles
  topic: section
subject: kiberxavfsizlik, inson omili, sun’iy intellekt, phishing, ijtimoiy muhandislik, xavfsizlik tizimlari, tahdidlarni aniqlash, avtomatlashtirish, SI algoritmlar
  topic: keywords
creator: Qurbonov Xurshid
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 520
ending page: 526
doi: 10.65164/y16nax15

KIBERXAVFSIZLIKDA INTELLEKTUAL TEXNOLOGIYALAR ROLI: SUN’IY INTELEKT VA ILG‘OR HIMOYA MEXANIZMLARI
type: item
description: Ushbu maqolada kiberxavfsizlik tizimlarida sun’iy intellekt va mashinaviy o‘qitish texnologiyalaridan foydalangan holda kiber-hujumlarni real vaqt rejimida aniqlash va ularga qarshi kurashish masalalari tahlil qilinadi. An’anaviy xavfsizlik tizimlari (Firewall, Antivirus) faqat ma’lum bo‘lgan tahdidlar bilan ishlagani sababli, "Zero-day" (noma’lum) hujumlariga qarshi ojizdir. Tadqiqot davomida tarmoq trafigini tahlil qiluvchi va anomaliyalarni aniqlovchi adaptiv model taklif etilgan. Olingan natijalar sun’iy intellekt asosidagi tizimlarning hujumlarni aniqlash tezligi va aniqligi an’anaviy usullardan sezilarli darajada yuqori ekanligini ko‘rsatdi.
subject: Articles
  topic: section
subject: kiberxavfsizlik, sun’iy intellekt, mashinaviy o‘qitish, kiber-hujum, anomaliyalarni aniqlash, DDoS hujumi.
  topic: keywords
creator: Sodikova Nigora
creator: Ishkuvatov Azizbek
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 516
ending page: 519
doi: 10.65164/fvcjxf37

AQLLI KIBERHIMOYA: MOBIL EKOTIZIMLARDA OFLAYN AI MODELLARINING SAMARADORLIGI
type: item
description: Ushbu ilmiy maqolada zamonaviy kiber-tahdidlarga qarshi kurashishda sun’iy intellekt (AI) texnologiyalarini integratsiya qilishning dolzarb masalalari tadqiq etiladi. Tadqiqot obyekti sifatida "Cyber Brother" mobil xavfsizlik majmuasi tanlab olingan bo‘lib, unda oflayn rejimda ishlovchi mashinali o‘rganish modellarining samaradorligi tahlil qilingan. Maqolada mobil qurilmalarni zararli dasturlardan (malware) himoya qilishning yangi metodologiyasi, real vaqt rejimidagi monitoring tizimlari va fishing hujumlariga qarshi "Red Alert" protokoli tavsiflangan. Olingan natijalar AI asosidagi avtonom tizimlarning an’anaviy metodlarga qaraganda yangi turdagi (zero-day) hujumlarni aniqlashda yuqori samaradorlikka ega ekanligini ko‘rsatadi.
subject: Articles
  topic: section
subject: Sun’iy intellekt, kiberxavfsizlik, Android, Cyber Brother, Malware tahlili, oflayn AI raqamli transformatsiya, kiber-hujum, Red Alert, Intent-Interception.
  topic: keywords
creator: Primbetov Abbaz
creator: Xamidov Xusniddin, Mamedov Kamron, Xakimov Muhammadillo
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 510
ending page: 515
doi: 10.65164/jqay7p69

SUN’IY INTELLEKTGA ASOSLANGAN IDS (HUJUMNI ANIQLASH TIZIMLARI) ORQALI KIBERHUJUMLARNI BARVAQT PROGNOZLASH
type: item
description: Mazkur tezisda sun’iy intellektga asoslangan IDS (Intrusion Detection System) tizimlari orqali kiberhujumlarni aniqlash va barvaqt prognozlash masalalari o‘rganilgan. Tadqiqot davomida CNN, LSTM, Autoencoder hamda CNN-LSTM gibrid modellari tahlil qilinib, ularning tarmoq trafikidagi fazoviy va vaqtga bog‘liq naqshlarni aniqlashdagi samaradorligi baholandi. Shuningdek, NSL-KDD, CICIDS va UNSW-NB15 kabi zamonaviy datasetlar asosida IDS modellarining ishlash samaradorligi o‘rganildi. Baholash jarayonida accuracy, precision, recall va F1-score kabi metrikalar qo‘llanildi. Natijalar shuni ko‘rsatadiki, chuqur o‘rganish modellariga asoslangan IDS tizimlari an’anaviy usullarga nisbatan yuqori aniqlik va prognozlash imkoniyatiga ega bo‘lib, ayniqsa CNN-LSTM gibrid modeli eng yaxshi natijalarni ko‘rsatdi, shuningdek tadqiqot natijalari IoT muhitida yengil IDS modellarining zarurligini tasdiqladi
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Sun’iy intellekt, IDS, kiberxavfsizlik, Deep Learning, CNN, LSTM, Autoencoder, CNN-LSTM, tarmoq trafik, anomaliya aniqlash, kiberhujum, prognozlash, NSL-KDD, CICIDS, UNSW-NB15, precision, recall, F1-score, IoT, time-series analysis.
creator: Turdimatov Mamirjon
creator: Sobirov Sherzodbek
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 504
ending page: 509
doi: 10.65164/0w5kv984

IMPROVING LEGAL MECHANISMS FOR DETECTING CYBERCRIMES BASED ON STATISTICAL ANALYSIS OF FINANCIAL TRANSACTIONS IN THE BANKING SYSTEM
type: item
description: The rapid expansion of digital banking has significantly increased the scale and complexity of cyber-enabled financial crimes. Traditional legal mechanisms often struggle to keep pace with evolving fraud patterns, particularly in real-time transaction environments. This paper proposes an integrated approach that combines statistical analysis of financial transactions with compliance-aware artificial intelligence to enhance cybercrime detection and legal accountability. By leveraging short-term behavioral patterns, anomaly detection, and regulatory-aligned decision frameworks, the study demonstrates how financial institutions can improve both detection accuracy and legal traceability. The findings highlight the importance of embedding explainability, auditability, and statistical evidence into cybercrime detection systems to support effective law enforcement and regulatory compliance.
subject: Articles
  topic: section
subject: card-not-present transactions, compliance aware, regulatory framework, fraud detection, artificial intelligence
  topic: keywords
creator: Akmalbek Abdusalomov
creator: Dilshodjon Egamberdiev
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 499
ending page: 503
doi: 10.65164/t6wnr026

ARTIFICIAL INTELLIGENCE AND CYBERSECURITY IN MODERN INFORMATION TECHNOLOGY EDUCATION
type: item
description: The rapid development of digital technologies has significantly influenced modern education systems, especially in the field of Information Technology. Artificial Intelligence (AI) and Cybersecurity have become critical areas shaping the future of digital infrastructure and data protection. Universities are increasingly integrating these technologies into IT education in order to prepare students for the modern digital economy. This study examines the role of Artificial Intelligence and Cybersecurity in information technology education. The research analyzes teaching methodologies, practical laboratory training, and digital learning tools used in universities. A qualitative research approach was applied by reviewing academic publications and international educational reports. The findings show that integrating AI tools, Cybersecurity training environments, and project-based learning improves students' technical competencies and analytical thinking skills. The study concludes that modern IT education should continuously evolve by adopting emerging technologies and innovative teaching strategies to prepare future technology professionals.
subject: Articles
  topic: section
subject: Artificial Intelligence, Cybersecurity, Information Technology Education, Digital Learning, Emerging Technologies.
  topic: keywords
creator: MARDIYEV RASULJON
creator: DINAKARAN SABAPATHY
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 495
ending page: 498
doi: 10.65164/vadsjt67

DEEPFAKE TEXNOLOGIYASINING KIBERXAVFSIZLIK TIZIMLARIGA TA’SIRI
type: item
description: Mazkur maqolada Deepfake texnologiyasining kiberxavfsizlik tizimlariga ta’siri tahlil qilingan. Unda deepfakeni yaratish usullari, xususan GAN va boshqa sun’iy intellekt modellari asosida ishlash prinsiplari yoritilgan. Shuningdek, ijtimoiy muhandislik hujumlari, biometrik autentifikatsiya tizimlariga tahdidlar va yolg‘on axborot tarqatish kabi xavflar misollar asosida ko‘rib chiqilgan. Maqolada ushbu tahdidlarga qarshi kurashish usullari, jumladan, aniqlash algoritmlari, ko‘p faktorli autentifikatsiya va huquqiyetik yondashuvlar bayon etilgan. Tadqiqot natijalari deepfake texnologiyalarining kiberxavfsizlikka ta’siri murakkab va ko‘p qirrali ekanligini ko‘rsatadi.
subject: Articles
  topic: section
subject: deepfake, sun’iy intellekt, kiberxavfsizlik, GAN, biometrik autentifikatsiya, yolg‘on axborot, ijtimoiy muhandislik, axborot xavfsizligi
  topic: keywords
creator: Latipov J.T
creator: Abdurahimov D.R
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 491
ending page: 494
doi: 10.65164/50kkpm75

KORXONA AXBOROT TIZIMLARIDA MA’LUMOTLAR ZAXIRA NUSXALARINING XAVFSIZLIGINI TA’MINLASHDA TAHDIDLAR VA ULARGA QARSHI ZAMONAVIY YECHIMLAR
type: item
description: Ushbu maqolada axborot tizimlarida zaxira jarayonining mohiyati, uning axborot xavfsizligini ta’minlashdagi o‘rni hamda zamonaviy tahdidlar sharoitidagi ahamiyati yoritilgan. Tadqiqotda ma’lumotlar yo‘qolishining oldini olish, ularni tiklash va tizim uzluksizligini ta’minlashga qaratilgan zaxira nusxalash tizimlarining asosiy funksiyalari tahlil qilingan. Shuningdek, ransomware, ichki tahdidlar, fizik nosozliklar va tarmoq hujumlari kabi asosiy xavf omillari ko‘rib chiqilib, ularning zaxira nusxalash tizimlariga ta’siri baholangan. Maqolada 3-2-1 qoidasiga asoslangan saqlash modeli, doimiy zaxira nusxalash, shifrlash va zero trust yondashuvi kabi zamonaviy himoya usullari ham tahlil qilingan. Natijada, zaxira nusxalash tizimlarining samaradorligini oshirish va axborot xavfsizligini mustahkamlash uchun kompleks yondashuv zarurligi asoslab berilgan.
subject: Articles
  topic: section
subject: zaxira nusxalash, zaxira nusxa, kiberxavfsizlik, ransomware, cloud storage, disaster recovery, ma’lumotlar himoyasi
  topic: keywords
creator: G‘aniyeva Shaxrizod
creator: Yo‘lchiboyeva Saxovatxon
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 487
ending page: 490
doi: 10.65164/15yrz493

GENERATIV SUN’IY INTELLEKT SHAROITIDA WEB-SESSIYA TOKENLARI XAVFSIZLIGINI TA’MINLASH, TAHDIDLAR VA HIMOYA MEXANIZMLARI
type: item
description: Ushbu maqolada generativ sun’iy intellekt rivojlanayotgan sharoitda web-sessiya tokenlari xavfsizligini ta’minlash masalalari tahlil qilinadi. Tadqiqot davomida session hijacking, XSS va CSRF kabi asosiy tahdidlar ko‘rib chiqilib, ularning sun’iy intellekt vositalari yordamida yanada murakkablashib borayotgani asoslab beriladi. Shuningdek, tokenlarni himoyalashning zamonaviy usullari, jumladan, HTTPS protokoli, cookie parametrlarini sozlash, token rotatsiyasi va qo‘shimcha autentifikatsiya mexanizmlari samaradorligi yoritiladi.
subject: Articles
  topic: section
subject: web-xavfsizlik, sessiya tokenlari, generativ sun’iy intellekt, XSS, CSRF, session hijacking, autentifikatsiya
  topic: keywords
creator: Umarov Shuxratjon
creator: Ahmadjonov Ahlidin
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 483
ending page: 486
doi: 10.65164/714fev72

AI ASOSIDAGI SIMULYATSIYALAR YORDAMIDA KIBERXAVFSIZLIKNI O‘QITISH: ETHICAL HACKING YONDASHUVINING SAMARADORLIGI VA XAVFSIZLIK MUAMMOLARI
type: item
description: Mazkur maqolada sun’iy intellekt asosidagi simulyatsiyalar orqali kiberxavfsizlikni o‘qitish samaradorligi tahlil qilinadi. Ethical hacking yondashuvi asosida tashkil etilgan o‘quv jarayonining talabalarning nazariy bilimlari va amaliy ko‘nikmalariga ta’siri eksperimental tarzda o‘rganildi. Natijalar AI simulyatsiyalari an’anaviy usullarga nisbatan samaraliroq ekanini ko‘rsatib, bilimni oshirish, analitik fikrlashni rivojlantirish va real kiberxavf stsenariylarini tushunishda muhim ahamiyatga ega ekanini tasdiqladi. Shuningdek, yondashuvning ayrim muammolari aniqlanib, ularni bartaraf etish bo‘yicha tavsiyalar berildi.
subject: Articles
  topic: section
subject: Kiberxavfsizlik, sun’iy intellekt, simulyatsiya, ethical hacking, ta’lim texnologiyalari, kiberhujum, penetration testing, adaptiv o‘qitish, virtual laboratoriya, kiberxavfsizlik ta’limi
  topic: keywords
creator: Sh.N.G‘aniyeva
creator: Z.U.Toxirjonova
rights: Copyright (c) 2026
date: 2026-05-15
publication date: 2026-05-15
starting page: 477
ending page: 482
doi: 10.65164/bsfm7s29