Raqamli texnologiyalar va iqtisodiyot: zamonaviy muammolari va istiqbollari mavzusida Respublika ilmiy-amaliy

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil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ikkita mumkin bo'lgan natijani qayd etadi, "1" va "0". “1” qiymati faollashtirish funksiyasini ishga tushiradi, “0” qiymati esa to’xtatish uchun xizmat qiladi. Perseptron ikkilik xarakterga IKEFS PWELEQ ]SOM FM^JESPPEWLXMVMWLJYROXWM]EWMRMWS^PEWLRMRKXYVPMYWYPPEVMQEZNYH Ushbu misolda faollashtirish funksiyasini ≥ 0 qilinishi kerak. Bu shuni anglatadiki, EKEV ]MK MRHM QYWFEX WSR ]SOM RSP FS PWE GLMUMWL ]MK MRHM QERJM] WSR FS PWE GLMUMWL FS PEHM 3PMRKERREXMNEPEV 7LYRHE]UMPMF /MVMWL! /MVMWL! =MK MRHM 7 ! 6EUEQPM UM]QEX RSPHER OMGLMO FS PWE REXMNE WMJEXMHE VS ]\EXKE SPMREHM ZE WLYRMRK YGLYRTIVWITXVSRRMRKJESPPEWLYZJYROXWM]EWMRMUS ^K EXQE]HM &MVSq, faollashtirish chegarasini to'liq o'zgartirish mumkin bo’lgan turli xil qoidalar mavjud. Masalan: x > 3, y = 1, x ≤ 3, y = 0 61

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil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

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil QSHIP IOWTSRIRX VEZMWLHE QYVEOOEFPEWLEHM ZE RI]VSR XEVQSUPEVHE FY OS TVSU OMVMWL XYKYRPEVMRMFSWLUEVMWLYGLYROS TVSUUEXPEQPEVRMERKPEXEHM&MVSUGLYUYVUEXPEQPMRI]VSR XEVQSU VEWQHE OS VWEXMPKERMHIO QYVEOOEF REUWLPEVRM SHHM]VSU REUWLPEVKE ENVEXMWLKE USHMV <YPSWE 9WLFY XI\RSPSKM]E ]SVHEQMHE XYrli xil xususiyatlarni aniqlash uchun bog’lamlardan JS]HEPERKERLSPHEHMEKSREPGLM^MUOEFM]Y^PEVRMXERMFSPMWLQYQOMR5YVMPMWLFPSOPEVMWMRKEVM XEVQSU OMVMWLRM QEWEPER SHEQRMRK ]Y^M ]SOM QYWLYORMRK ]Y^M WMJEXMHE XEWRMJPEWL YGLYR XYKYRREXMNEPEVMRMFMVPEWLXMVEHMZEOI]MRQE PYQFMVWLE\WRMRK]Y^MRMXERMFSPMWLYGLYRUE]XE MWLPE]HM 4M]SHEPEV ZE FSWLUE XVERWTSVX ZSWMXEPEVM OEFM SF IOXPEVRM XERMF SPMWL YGLYR S ^ S ^MHERFSWLUEVMPEHMKERXVERWTSVX ZSWMXEPEVMXSQSRMHERUS PPERMPEHMKERSF IOXRM XERMFSPMWL FYgungi kunda keng tarqalgan yo’nalishlardan xisoblanadi. Аdabiyotlar 2IEVWLSVI%QIVMGEW1EGLMRI0IEVRMRK%HSTXMSR8L[EVXIHF]0EGOSJ7OMPPWERH 9RHIVWXERHMRKLXXT[[[RIEVWLSVIEQIVMGEWGSQ %VXLYV7EQYIP7SQI7XYHMIWMR1EGLMRI0IEVRMRK9WMRKXLI+EQISJ'LIGOIVW -&1.SYVREPSJ6IWIEVGLERH(IZIPSTQIRX:SP-WWYI %VXLYV7EQYIP7SQI7XYHMIWMR1EGLMRI0IEVRMRK9WMRKXLI+EQISJ'LIGOIVW -&1.SYVREPSJ6IWIEVGLERH(IZIPSTQIRX:SP-WWYI (EXE:MWSV 9RWYTIVZMWIH 1EGLMRI 0IEVRMRK LXXTW[[[HEXEZMWSVGSQYRWYTIVZMWIHQEGLMRIPIEVRMRKIRKMRI )RKMRI /IZMR/IPP]8LI-RIZMXEFPI9RHIVWXERHMRKXLI8IGLRSPSKMGEP*SVGIW8LEX;MPP 7LETI3YV*YXYVI4IRKYMR&SSOW 63

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil MA’LUMOTL%6+%-28)00)/89%0-7,03:&)6-7,2-2+/0%78)60%7,:% 8%72-*0%7,97900%6- )PFIO>EVQEWSZ 1YLEQQEHEP<SVE^QM]RSQMHEKM8SWLOIRXE\FSVSXXI\RSPSKM]EPEVMYRMZIVWMXIXMOEXXE o‘qituvchisi ^EVQEWSZIPFIO$QEMPVY %RRSXEXWM]E Ushbu ishda ma’lumotlarni intellektual tahlil qilish, axborot kommunikasit texnologiyalari evolutsiyasi va ma’lumotlarga intellaktual ishlov berish potentsiali, Data Mining tushunchasi va uning qo‘llanish sohasi, IBM Big Data TPEXJSVQEPEVMRMRK \YWYWM]EXPEVM -&1 -RJS7TLIVI &MK-RWMKLXW TPEXJSVQEWM ZE YRMRK MQOSRM]EXPEVM -&1 -RJS7TLIVI 7XVIEQW TPEXJSVQEWM ZE YRMRK MQOSRM]EXPEVM OEFM RE^EVM] FMPMQPEVXELPMPUMPMRKER Kalit so‘zlar: An’anaviy SQL ma’lumotlar bazalarini, data mining tizimlarini qo‘llash QYZEJJEUM]EXM WLYRHER MFSVEXOM PSKMWXMO VIKVIWWM]E FY PSKMWXMO JYROXWM]E QSHIPMKE asoslangan tasniflash usuli, training ma’lumotlari FY XEWRMJPEWL QSHIPMRM ]EVEXMWL YGLYR foydalaniladigan ma’lumotlar. So‘nggi paytlarda juda katta ma’lumotlar to‘plamlari va klaster miqyosli ma’lumotlarni qayta ishlash imkoni paydo bo‘ldi, bu esa guruhlar va ma’lumotlar xaritalari bo‘yicha ma’lumotlarni qazib olish natijalarini yanada murakkab umumlashtirish imkonini beradi. &YKYRKMOYRHEFMVPEWLXMVMPKERWEUPEWLZEUE]XEMWLPEWh tizimlarini o‘z ichiga olgan mutlaqo ]ERKMZSWMXEPEVZEXM^MQPEVQEZNYH An’anaviy SQL ma’lumotlar bazalarini, xom matn ma’lumotlarini, kalitlar/qiymatlar to‘plamini va hujjat bazalarini o‘z ichiga olgan turli xil ma’lumotlar to‘plamlarini tahlil UMPMWLMRKM^ QYQOMR ,EHSST 'EWWERHVE 'SYGL(& ZE 'SYGLFEWI 7IVZIV OEFM OPEWXIVPM ma’lumotlar bazalari ma’lumotlarni an’anaviy jadval tuzilishiga rioya qilmaydigan tarzda WEUPE]HMZEYPEVKEOMVMWLMQOSRMRMFIVEHM 7XERHEVX .732 XMTMHEKM XY^MPQEKE QSW OIPEHMKER LYjjat ma’lumotlar bazalari yoki ba’zi bir mashina o‘qiy oladigan tuzilishga ega fayllarni qayta ishlash ham oson, garchi o‘zgaruvchan va o‘zgaruvchan tuzilma ishlarni qiyinlashtirishi mumkin. Masalan, butunlay “xom” ma’lumotlarni qayta ishlovchi Hadoop’da ma’lumotlarni qayta ishlash va solishtirishdan oldin uni aniqlash va olish qiyin bo‘lishi mumkin. Data Mining tizimlarini qo‘llash muvaffaqiyati shundan iboratki, bu texnologiyalar empirik ma’lumotlarni o‘rganish ta’minlaydi, ya’ni ular quyidagi vazifalarni LEP UMPMWLRM ta’minlaydi: 8EWRMJPEWL yangi ob‘ektni ma’lum bir sinfga kiritish uchun bir xil turdagi ob‘ektlarning belgilarini aniqlash vazifasi. 8EWRMJPEWL bu mashinani o‘rganish vazifasi bo‘lib, unda taqdim etilgan o‘quv ma’lumotlari asosida ob‘ektlar yoki ma’lumotlarni oldindan belgilangan sinflar yoki toifalarga ajratish uchun model o‘rgatiladi. Tasniflash ma’lumotlarni tahlil qilishning eng OIRKXEVUEPKERZEQYLMQYWYPPEVMHERFMVMHMV Ba’zi mashhur tasniflash usullari quyidagilarni o‘z ichiga oPEHM 64

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil 0SKMWXMO VIKVIWWM]E &Y PSKMWXMO JYROXWM]E QSHIPMKE EWSWPERKER XEWRMJPEWL YWYPM Logistik regressiya ob‘ektning ma’lum bir sinfga tegishli bo‘lish ehtimolini bashorat qiladi va XEWRMJPEWLUEVSVMRMUEFYPUMPMWLYGLYRGLIKEVEUM]QEXMHERJS]HEPEREHM 5Eror daraxtlari: Bu ma’lumotlar xususiyatlariga asoslangan qaror qoidalarining ierarxik tuzilishini yaratadigan tasniflash usuli. Qaror daraxtlari ma’lumotlar maydonini turli WMRJPEVKEQSWOIPEHMKERXYVPMQMRXEUEPEVKEENVEXEHM Vektor mashinasini qo‘llabUYvvatlash (SVM): Bu ma’lumotlar sinflarini ajratuvchi KMTIVTPER GLM^MU XIOMWPMO ]SOM KMTIVTPER UYVEHMKER XEWRMJPEWL YWYPM 7:1 GLIKEVERM QEOWMQEP HEVENEHE SWLMVMWLKE UEVEXMPKER KMTIV XIOMWPMO ZE XYVPM WMRJPEVRMRK IRK ]EUMR ob‘ektlari orasidagi masofa). 2EMZI &E]IW OPEWWMJMOEXSVM &Y &E]IW XISVIQEWMKE EWSWPERKER ILXMQSPPM XEWRMJPEWL usuli. Naive Bayes klassifikatori ma’lum bir sinfga mansub ob‘ektning ehtimolliklarini QSHIPPEWLXMVEHMZEXEWRMJPEWLIRK]YUSVMILXMQSPPMOEWSWMHEEQEPKESWLMVMPEHM 8EWRMJPEWLQSHIPM =YUSVMHEKM NEHZEPHEKM HEWXPEFOM FIWLXE YWXYRHE XEWRMJPEWL QSHIPMRM ]EVEXMWLKE yordam beradigan haqiqiy ma’lumotlar mavjud. Tasniflash modeli jadvaldagi raqamlarni o‘rganadi va qanday yorliq bilan bog‘liq bo‘lgan xususiyatlarning qanday kombinatsiyEWM LEUMHEQEXIQEXMOYQYQPEWLXMVMWLRMXEOPMJUMPEHM Klassifikator: Model qurilgandan so‘ng, tasniflagich yorlig‘i noma’lum bo‘lgan har qanday yangi ma’lumot nuqtasi uchun yorliqni bashorat qilish uchun tasniflash modelidan JS]HEPEREHM1MWSPYGLYRUY]MHEgi jadvalda bizda to‘rtta yangi bemor haqida ma’lumot bor, lekin bizda "Infected" yoki "Infected" kabi sinf belgilari mavjud emas. Tasniflash topshirig‘ida klassifikator tasniflash modelidan (oldindan yorliqli ma’lumotlardan tuzilgan, masalan, SPHMRKM NEHZal) quyidagi jadval kabi sinf yorlig‘i mavjud bo‘lmagan ma’lumotlarning sinf FIPKMPEVMRMFEWLSVEXUMPMWLYGLYRJS]HEPEREHM /PEWXIVPEWLob‘ektlar sinflarining o‘zlari oldindan belgilanmagan, ammo vazifa bir hil ma’lumotlar guruhlarini aniqlashdan iborat bo‘lgan murakkabroq holat uchun tasniflash g‘oyasini ishlab chiqish. /PEWXIVPEWLbu sizga o‘xshash ob‘ektlar yoki ma’lumotlarni klasterlar deb ataladigan to‘plamlarga guruhlash imkonini beruvchi nazoratsiz mashinani o‘rganish usuli. Klasterlash ma’lumotlardagi yashirin tuzilmalar va naqshlarni aniqlash va ma’lumotlarni tahliliy tahlil UMPMWLYGLYRMWLPEXMPEHM Ba’zi mashhur klasterlash usullari quyidagilarni o‘z ichiga oladi: /QIERW /means): Bu eng mashhur klasterlash usullaridan biridir. U ob‘ektlaV ZE klasterlarning markazlari (o‘rta nuqtalari) orasidagi kvadrat masofalar yig‘indisini minimallashtirish uchun ma’lumotlarni oldindan belgilangan klasterlar soniga (K) ajratadi. -IVEV\MO OPEWXIVPEWL &Y YWYP OPEWXIVPEV MIVEV\M]EWMRM ]EVEXEHM FYRHE LEV bir ob‘ekt alohida klasterda boshlanadi va keyin ular orasidagi o‘xshashlik o‘lchovi asosida klasterlarni birlashtiradi yoki ajratadi. Ierarxik klasterlash aglomerativ (pastdan yuqoriga) yoki bo‘linish (yuqoridan pastga) bo‘lishi mumkin. DBSCAN: Bu ma’lumotlar zichligiga asoslangan klasterlash usuli. U klasterlarni past 65

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil ^MGLPMOHEKMNS]PEVFMPERENVEXMPKER]YUSVM\YWYWM]EXPM^MGLPMOHEKMLYHYHPEVWMJEXMHEFIPKMPE]HM DBSCAN o‘zboshimchalik bilan shakllangan klasterlarni aniqlay oladi va chet IPPMOPEVRM (anomal ob‘ektlar) qayta ishlaydi. Affinity Propagation: Bu usul ob‘ektlar orasidagi xabarlarni uzatishga tayanadi. U "namunalar" bo‘lgan ob‘ektlarni aniqlash orqali klasterlarni belgilaydi va ularning klaster a’zoligini yangilash uchun boshqa ob‘ektlarga xabarlar yuboradi. Bu klasterlash usullarining faqat bir qismi va har birining o‘ziga xos xususiyatlari va taxminlari bor. Usulni tanlash ma’lumotlarning xususiyatlariga va tahlil maqsadlariga bog‘liq. %WWSXWMEXWM]EPEVRM ERMUPEWL FMV hodisaning ma’lum bir ehtimollik bilan sodir bo‘lganda, ikkinchisi sodir bo‘lishini ko‘rsatadigan qoidalarni o‘rnatish. %WWSXWMEXWM]E ERMUPEWL bu katta ma’lumotlar to‘plamidagi o‘zgaruvchilar yoki elementlar o‘rtasidagi statistik munosabatlar va naqshlarRM XSTMWLKE UEVEXMPKER ma’lumotlarni tahlil qilish usuli. Bu sizga qaysi elementlarning teztez birga bo‘lishini yoki qaysi atributlar bog‘liqligini aniqlash imkonini beradi. %HEFM]SXPEV Бабенко М. А., Левин М. В. Введение в теорию алгоритмов и структур данных. —М.: МЦНМО. 2020. 144 с. Бенгфорт, Б. Прикладной анализ текстовых данных на Python. Машинное обучение и создание приложений обработки естественного языка / Б. Бенгфорт. —СПб.: Питер, 2019. —G Гашев С. Н. Математические методы в биологии: анализ биологических данных в системе Statistica. —М.: Юрайт. 2020. 208 с. Козлов А.Ю. Статистический анализ данных в MS Excel: Учебное пособие А.Ю.Козлов, В.С. Мхитарян, В.Ф. Шишов. —М.: ИнфраМ, 2018. —G 66

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Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil Методы анализа данных: Data Mining, Visual Mining, Text Mining / А. А. Барсегян, М. С. Куприянов, В. В. Степаненко, И. И. Холод // OLAP. 2е изд., перераб. и доп. СПб.: БХВПетербург, 2007. 76

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil MOBIL QURILMALARDAGI MA’LUMOTLARNI CLOUDDA XAVFSIZ SAQLASH ALGORITMI 3HMPFIO%WUEVEPM]IZ7EQERHEV=YWYTSZ7MVSNMHHMR<EPMPSZ Perfect universiteti akdemik faoliyat bo‘yicha prorektori 9RMZIVWMX]SJ1EREKIQIRXERH*YXYVI8IGLRSPSKMIWYRMZIVWMXIXMQEKMWXVERXM %PJVEKERYWYRMZIVWMXIXM6EUEQPMXE\RSPSKM]EPEVOEJIHVEWMEWWMWXIRXM OLWYVENMHHMR$KQEMPGSQ %RRSXEXWM]E9WLFYMPQM]XEHUMUSXMWLMHEE\FSVSXRMOVMTXSKVEJMOLMQS]EPEWLXM^MQPEVM RE^EVM]EWM ILXMQSPPEV RE^EVM]EWM WSRPEV RE^EVM]EWM QEXIQEXMO QERXMU ZE OSQFMREXSVMOE QIXSHPEVMHER JS]HEPERMPKER &YPEVHER XEWLUEVM WSPMWLXMVMWL XIWXPEWL ZE UM]SWM] XELPMP usullaridan foydalanildi. Mobil qurilamalardagi ma’lumotlarni xavfsizligini ta’minlash, Cloud Storageda ma’lumotPEVRMLMQS]EPEWLZE'PSYH7XSVEKIXI\RSPSKM]EWMHEQEZNYH^EMJPMOPEVRM FEVXEVEJ IXMWLKE UEVEXMPKER \EZJWM^PMO GLSVEPEVMRM MWLPEF GLMUMWL MWLMRMRK RE^EVM] ELEQM]EXM sanaladi. Ma’lumotlarni himoyalashning mujassamlashgan usulidan foydalangan holda QSFMPUYVMPEQEPEVHEWEUPEREHMKERZEMWLPEREHMKERE\FSVSXPEVRM'PSYH7XSVEKIXI\RSPSKM]EWM EWSWMHELMQS]EPEWLWEQEVEHSVPMKMRMSWLMVMWLKEUEVEXMPKEREPKSVMXQPEVMWLPEFGLMUMPHM Kalit so‘zlar: 'PSYH GSQTYXMRK 'PSYH 7XSVEKI %)7 ZE 7%07% 7,% ZE 1( WLMJVPEWL'PSYHHE\EZJWM^(IWLMJVPEWLEPKSVMXQM /MVMWL ,S^MVKM OYRHE LE]SXMQM^RM QSFMP UYVMPQEPEV MRXIVRIX YQYQER SPKERHE E\FSVSX XI\RSPSKM]EPEVMWM^XEWEZZYVIXMWLUM]MR9PEVLE]SXMQM^RMRKENVEPQEWUMWQMKEE]PERMFYPKYVHM Ularning rivojlanishi natijasida ma’lumotlaVMQM^RM WEUPEWL ZE YPEVHER JS]HEPERMWL imkoniyatlari oshib bormoqda. Biz doimiy ravishda mobil qurilmalarimizda o‘zimiz uchun kerakli bo‘lgan axborotlarimi saqlaymiz, vaqti kelganida ularni kimgadir yuboramiz va OMQHERHMVUEFYPUMPMFSPEQM^ &YRHER XEWLUEVM FYPYXPM LMWSFPEWL XI\RSPSKM]EPEVM 'PSYH GSQTYXMRK VMZSNPERMWLM natijasida biz o‘z ma’lumotlarimizni bulutli serverlarda ya’ni Cloud Storagelarda [1] saqlash MQOSRM]EXMHEROIRKJS]HEPERQSUHEQM^ 'PSYH GSQTYXMRK IPIOXVSR LMWSFPEWL \M^QEXPEVMRM OSQT]YXIV XEVQSUPEVM SVUEPM yetkazib berishni nazarda tutadi va o‘zida ma’lumotlarni saqlash tizimlari, turli ilovalar uchun platformalar, katta hisoblashlarni internet tarmog‘ida mavjud kompyuterlardan foydalanib ]IGLMWLOEFMMQOSRM]EXPEVRM]EVEXEHM &YPYXPMXI\RSPogiyalar qulayliklar yaratish bilan bir qatorda muammolarni ham o‘rtaga qo‘ymoqda. Ushbu texnologiya mavjud imkoniyatlar bilan birgalikda Cloud Storageda saqlanayotgan ma’lumotlar xavfsizligini ta’minlash masalasini keltirib chiqarmoqda. 1EXIVMPPEVZEYWYPPEV Yuqorida aytib o‘tilganidek, mobil qurilmalardagi ma’lumotlarni Cloudda xavfsiz WEUPEWLHEWXYVMRMMWLPEFGLMUMWLYGLYR%)7ZE7%07%WLMJVPEWLEPKSVMXQPEVMLEQHE7,% va MD5 heshlash funsiyalaridan foydalanilgan bo‘lib, ulardan mujasWEQPEWLKER LSPHE JS]HEPERMWL SVUEPM QSFMP UYVMPQEPEVHE WEUPEREHMKER ZE MWLPEREHMKER E\FSVSXPEVRM 'PSYH 7XSVEKI XI\RSPSKM]EWM EWSWMHE LMQS]EPEWL WEQEVEHSVPMKMRM SWLMVMWL QYQOMR 1E^OYV QYNEWWEQPEWLKERYWYPSVUEPMUY]MHEKMQYEQQSPEVLEPIXMPKER 77

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil − − − − − *S]HEPERYZGLMPEVRMEYXIRXMJMOEXWM]EPEWL JE]PRSQMZEQE^QYRMRMSWLOSVIXQEWPMO JE]PRMRKOMQKEXIKMWLPMIOERPMKMRM]EWLMVMWL FMVQEVXEPMOOEPMXPEVHERJS]HEPERMWL ma’lumotlarni serverda shifrlangan ko‘rinishda saqlash. *S]HEPERYZGLMPEVRM EYXIRXMJMOEXWM]EPEWLHE JS]HEPERYZGLMRMRK RSQM QSFMP UYVMPQEHE ro‘yhatdan o‘tgan pochta manzili orqali unga ulanish paroli esa, shifrlash kalitidan foydalangan holda faylda saqlanadi. Ushbu parol joylashgan faylni ma’lumot tashuvchi UYVMPQEHE WEUPEWL ]SOM FYPYXPM WIVZIVPEVHE WEUPEWL QYQOMR 9WLFY NEVE]SRRM EQEPKE oshirish natijasida, klaviatura va qo‘pol kuch hujumlaridan oldi olinadi[56]. *E]PRMRK OMQKE XIKMWLPM IOERPMKMRM ]EWLMVMWL Ya’ni, faylning o‘zi shifrlangan holda 'PSYHKE ]YFSVMPEHM *S]HEPERYZGLM IQEMPPEVMHER IWE \IWL UM]QEXM LMWSFPERMF YRKE shifrlangan kalit qo‘shiladi va u ham Cloudda saqlash uchun yuboriladi. Hosil bo‘lgan hesh qiymat tasodifiy belgilardan iborat bo‘lib, u kimga tegishli ekanligini o‘zida berkitib turadi. &MVQEVXEPEPMOOEPMXPEVHERJS]HEPERMWLBir martalik kalitlar har bir to‘plam nomi orqali yaratiladi. Ushbu kalit AES shifrlash algoritmi yordamida shifrlanadi va hosil bo‘lgan kalitni foydalanuvchi uchun tushunarli bo‘lgan joyda saqlab qo‘yiladi. Faylga har safar murojaat bo‘lganida ushbu faylyangisiga o‘zgaradi. Ya’ni bir kalit faqat bir marta qo‘llaniladi. Ma’lumotlarni serverda shifrlangan ko‘rinishda saqlashda 7%07% EPKSVMXQMHER JS]HEPERMPEHM 9RHE OEPMX WMJEXMHE ]YUSVMHE %)7 ]SVHEQMHE WLMJVPEF JE]PHE WEUPERKER XEWSHMJM]FMVQEVXEPMOOEPMt qo‘llaniladi. VEWQ(EWXYVEPKSVMXQM Dasturga kirgandan so‘ng, dastlab foydalanuvchidan maxfiy parolni kiritish so‘raladi. %KEVTEVSP\EXSOMVMXMPWEHEWXYVHERJS]HEPERMWLKEVY\WEXFIVMPQE]HM 78

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil - Agar parol to‘g‘ri kiritilsa, dastur keying bosqichga o‘tEHM9RHEUY]MHEKMPEVRMEQEPKE SWLMVMWLQYQOMR Maxfiy parolni o‘zgartirish; Ma’lumotlarni shifrlab Cloudga yuborish va deshifrlash uchun kerakli bo‘lgan qiymatlarni saqlab qo‘yish; Ma’lumotlarni Clouddan yuklab olish va ularni deshifrlab, JS]HEPERYZGLMKEXEUHMQIXMWL Shifrlash algoritmini ko‘radigan bo‘lsak, unda quyidagi ketmaOIXPMOPEVFENEVMPEHM VEWQMa’lumotlarni shifrlab, Cloudga yuborish Bunda, quyidagilarni izohlab o‘tish zarur: R–to‘plam nomi; I–JS]HEPERMWLVY\WEXMFIVMPKan electron pochtalar, ular bir nechta bo‘lishi mumkin; J – xavfsizligi ta’minlanishi kerak bo‘lgan fayllar, ular shifrlanib, Cloud serverda WEUPEREHM 7EPWE–ma’lumotlarni shifrlash uchun ishlatiladigan algoritm, to‘liq nomi Salsa20; %)7 – WLMJVPEWLHE MWhlatilgan kalitni maxfiyligini ta’minlash uchun foydalaniladigan WLMJVPEWLEPKSVMXQM 1(WLE–\IWLJYROWM]EPEV Dastlab kirish qiymati sifatida, to‘plam nomi, foydalanish ruxsati berilishi kerak bo‘lgan emaillar va konfidensialligi ta’minlanishi kerak bo‘lgan fayllar tanlanadi. So‘ngra, belgilangan fayllar maxsus algoritm orqali shifrlanadi va belgilangan serverga yuboriladi. Shifrlashda ishlatilgan kalit esa, to‘plam nomi bilan birgalikda AES WLMJVPEWLEPKSVMXQMSVUEPMWLMJVPEREHM Keyin undan xesh qiymat olinib, ruxsat berilgan har bir emailga qo‘shilgan holda yana FMVFSV\IWLUM]QEXPEVLSWMPUMPMREHM9WLFYLIGLUM]QEXPEVRMRKLEVFMVMKEWLMJVPERKEROEPMX 79

Respublika ilmiy-amaliy konferensiyasi 24-25-aprel, 2024-yil FMVMOXMVMPMFYPEVLEQFIPKMPERKERWIVZIVHEWEUPEWLYGLYR]YFSVMPEHM /I]MRKi algoritm Clouddan ma’lumotlarni yuklab olish va deshifrlab foydalanuvchiga taqdim etish bo‘lib, 28VEWQHEOIPXMVMPKER Aytish mumkinki bu bundan oldingi algoritmni aksi bo‘lib, unda ham yuqorida OIPXMVMPKERWLMJVPEEWLEPKSVMXQPEVMZE\IWLPEWLJYROWM]EPEVMHERJS]HEPERMPKER Shuni ta’kidlab o‘tish lozimki, deshifrlash jarayonida hech qanday qiymat klaviatura orqali kiritlmaydi, ya’ni, algoritmda ko‘rsatilgan akey va e qiymatlar mobil qurilmadan olinadi. %RMUVSUUMPMFE]XKERHEEOI]WLMJVPEWLNEVE]SRMHEQSFMl qurilmaga maxsus saqlab qo‘yilgan kalit bo‘lib, u mobil qurilma xotirasidan ko‘rsatib qo‘yiladi. E esa mobil qurilmada autentifikatsiyadan o‘tgan electron pochta bo‘lib, emailni kiritish paytida, mobil qurilmadagi electron pochtalar ro‘yxati tqadim etiladi va ulardan birini tanlash so‘raladi[55]. VEWQ(IWLMJVPEWLEPKSVMXQM Deshifrlash jarayoni qachonki foydalanuvchi o‘zini haqiqiyligini tasdiqlagandagina amalga oshiriladi. Buning uchun, foydalanuvchi o‘zining haqiqiyligini, unga JS]HEPERMWL VY\WEXMFIVMPKERPMKMRM ZEYRHEQE\WYWOEPMXJE]PQEZNYHIOERPMKMRMXEWHMUPEWLMXEPEFIXMPEHM Agar foydalanuvchi ularni to‘g‘ri taqdim eta olmasa, deshifrlash jarayoni amalga SWLMVMPQE]HM <YPSWE Tadqiqot ishida mobil qurilmalardagi ma’lumotlaVRM 'PSYHHE \EZJWM^ WEUPEWL dasturini ishlab chiqishga qaratilgan bo‘lib, quyidagi natijalar olindi: Ma’lumotlarni Cloudda xavfsiz saqlash dasturida foydalanilgan shifrlash EPKSVMXQPEVMZE\IWLPEWLJYROWM]EPEVMXEHUMUIXMPHM IXMPHM 1E^OYV WLMJVPEWL EPKSVMXQPEVMRMRK EWSWMRM XEWLOMP IXYZGLM JYROWM]EPEV XEHUMU (EWXYVEPKSVMXQM]EVEXMPHM Yaratilgan algoritm asosida mobil qurilmalardagi ma’lumotlarni Cloudda xavfsiz saqlash dasturiy ta’minoti ishlab chiqildi; 80