Deep learning usullari va ularning kriptotahlil masalalarida qo'llanilishi
Deep learning usullari va ularning kriptotahlil masalalarida qo'llanilishi
Ushbu maqolada chuqur o'rganish (deep learning) texnikalarining zamonaviy kriptotahlil jarayonlarida qo'llanilish imkoniyatlari nazariy va eksperimental jihatdan tahlil qilingan. An'anaviy kriptoanaliz usullari kalit, ochiq matn va shifr matni o'rtasidagi murakkab chiziqsiz bog'lanishlarni aniqlashni talab qilgani sababli yuqori hisoblash murakkabligiga ega. Deep learning esa xom ma'lumotlar bilan bevosita ishlash, xususiyatlarni mustaqil ravishda ajrata olish va biaslarni avtomatik aniqlash kabi ustunliklari sababli kriptotizimlarning zaifliklarini topishda samarali vosita sifatida namoyon bo'lmoqda. Tadqiqotda oqimli shifrlar — RC4, uning takomillashtirilgan varianti RC4A, shuningdek Trivium va TRIAD algoritmlarining hosil qilgan keystreamlari "qora quti" modeli asosida chuqur neyron tarmoqlar orqali tahlil qilindi.
- TASHKENT KIMYO INTERNATIONAL UNIVERSITY Uzbekistan
- National University of Uzbekistan Uzbekistan
Chuqur O'rganish, Black-Box Modeli, Keystream, Kriptografiya., Trivium, Differensial Kriptoanaliz, Yon Kanal Tahlili, Konvolyutsion Neyron Tarmoqlar (CNN), TRIAD, Deep Learning, Mashinali O'qitish, Oqimli Shifrlash, Bias Aniqlash, Neyron Tarmoqlar, Rekurrent Neyron Tarmoqlar (RNN), LSTM, Kriptotahlil, RC4, RC4A
Chuqur O'rganish, Black-Box Modeli, Keystream, Kriptografiya., Trivium, Differensial Kriptoanaliz, Yon Kanal Tahlili, Konvolyutsion Neyron Tarmoqlar (CNN), TRIAD, Deep Learning, Mashinali O'qitish, Oqimli Shifrlash, Bias Aniqlash, Neyron Tarmoqlar, Rekurrent Neyron Tarmoqlar (RNN), LSTM, Kriptotahlil, RC4, RC4A
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