1. Lingaliro la Data Masking
Kusunga deta kumadziwikanso kuti masking data.Ndi njira yaukadaulo yosinthira, kusintha kapena kubisa deta yodziwika bwino monga nambala ya foni yam'manja, nambala yamakhadi aku banki ndi zidziwitso zina tikapereka malamulo ndi mfundo zobisika.Njirayi imagwiritsidwa ntchito makamaka pofuna kuteteza deta yovuta kuti isagwiritsidwe ntchito mwachindunji m'malo osadalirika.
Mfundo Yosunga Ma data: Kusunga deta kuyenera kukhalabe ndi zomwe zidayambira, malamulo amabizinesi, komanso kufunikira kwa data kuwonetsetsa kuti chitukuko, kuyesa, ndi kusanthula deta sikukhudzidwa ndi masking.Onetsetsani kusasinthasintha kwa data ndi kutsimikizika musanayambe kapena pambuyo pobisala.
2. Gulu la Data Masking
Kuyika kwa data kumatha kugawidwa kukhala static data masking (SDM) ndi dynamic data masking (DDM).
Static Data masking (SDM): Kusunga deta mosasunthika kumafuna kukhazikitsidwa kwa nkhokwe yatsopano yosapanga kuti ikhale yodzipatula ku malo opanga.Deta yachidziwitso imachotsedwa muzosungirako zopangira ndikusungidwa munkhokwe yosapanga.Mwanjira iyi, deta yodetsedwa imasiyanitsidwa ndi malo opangira, omwe amakwaniritsa zosowa zamalonda ndikuonetsetsa chitetezo cha deta yopanga.
Dynamic Data masking (DDM): Nthawi zambiri amagwiritsidwa ntchito m'malo opangira kuti asamve chisoni pa nthawi yeniyeni.Nthawi zina, magawo osiyanasiyana a masking amafunikira kuti muwerenge zomwe zili tcheru nthawi zosiyanasiyana.Mwachitsanzo, maudindo osiyanasiyana ndi zilolezo zitha kukhazikitsa masinthidwe osiyanasiyana.
Lipoti la data ndi zinthu zobisika zomwe zimagwiritsidwa ntchito
Izi makamaka zimaphatikizapo zinthu zowunikira data mkati kapena zikwangwani, zinthu za data zakunja zantchito, ndi malipoti otengera kusanthula deta, monga malipoti abizinesi ndi kuwunika kwa polojekiti.
3. Data Masking Solution
Njira zodziwika bwino za masking a data ndi: kusavomerezeka, mtengo wandalama, kusintha kwa data, kubisa kofananira, mtengo wapakati, kuchotsera ndi kuzungulira, ndi zina zambiri.
Kusavomerezeka: Kusavomerezeka kumatanthawuza kubisa, kudulidwa, kapena kubisa deta yodziwika bwino.Chiwembuchi nthawi zambiri chimalowetsa deta yeniyeni ndi zizindikiro zapadera (monga *).Ntchitoyi ndi yosavuta, koma ogwiritsa ntchito sangathe kudziwa mtundu wa deta yoyambirira, zomwe zingakhudze mapulogalamu otsatila.
Mtengo Wachisawawa: Mtengo wachisawawa umatanthawuza kusinthidwa mwachisawawa kwa deta yodziwika bwino (nambala m'malo mwa manambala, zilembo m'malo mwa zilembo, ndi zilembo m'malo mwa zilembo).Izi masking njira kuonetsetsa mtundu wa deta tcheru pamlingo wakutiwakuti ndi kutsogolera wotsatira deta ntchito.Kuphimba madikishonale kungafunike pa mawu ena atanthauzo, monga mayina a anthu ndi malo.
Kusintha Data: Kusintha kwa deta kumakhala kofanana ndi kubisa zikhalidwe zopanda pake komanso zopanda pake, kupatula kuti m'malo mogwiritsa ntchito zilembo zapadera kapena zikhalidwe zachisawawa, masking data imasinthidwa ndi mtengo wake.
Symmetric Encryption: Symmetric encryption ndi njira yapadera yosinthira masking.Imasunga deta yodziwika bwino kudzera pa makiyi achinsinsi komanso ma aligorivimu.Mawonekedwe a ciphertext akugwirizana ndi deta yoyambirira mu malamulo omveka.
Avereji: Chiwembu chapakati nthawi zambiri chimagwiritsidwa ntchito pazowerengera.Kuti tipeze manambala, timawerengera kaye tanthauzo lake, ndiyeno timagawira mwachisawawa zikhalidwe zomwe zimadetsedwa mozungulira tanthauzo, motero timasunga kuchuluka kwa datayo mosasintha.
Offset ndi Rounding: Njirayi imasintha deta ya digito ndikusintha mwachisawawa.Kuzungulira kozungulira kumatsimikizira pafupifupi kutsimikizika kwamtunduwo ndikusunga chitetezo cha deta, chomwe chili pafupi ndi deta yeniyeni kuposa ndondomeko zam'mbuyomu, ndipo zimakhala ndi tanthauzo lalikulu pazochitika za kusanthula kwakukulu kwa deta.
Recommend Model "ML-NPB-5660"kwa Data Masking
4. Njira Zomwe zimagwiritsidwa ntchito pa Data Masking Techniques
(1).Njira Zowerengera
Sampling ya data ndi kusonkhanitsa deta
- Zitsanzo za data: Kusanthula ndi kuwunika kwa deta yoyambirira yomwe idakhazikitsidwa posankha gulu laling'ono loyimilira la seti ya data ndi njira yofunikira yopititsira patsogolo luso la njira zodziwikiratu.
- Kuphatikizika kwa data: Monga njira zowerengera zowerengera (monga kuwerengera, kuwerengera, kuwerengera, kuchuluka ndi kuchepera) komwe kumagwiritsidwa ntchito kuzinthu zomwe zili mu microdata, zotsatira zake zimayimira zolembedwa zonse zomwe zili muzoyambira zoyambira.
(2).Zojambulajambula
Cryptography ndi njira yodziwika bwino yochepetsera mphamvu kapena kukulitsa mphamvu yakuchotsa chidwi.Mitundu yosiyanasiyana ya ma aligorivimu a encryption imatha kukwaniritsa zotsatira zosiyanasiyana.
- Deterministic encryption: Kubisa kosagwirizana mwachisawawa.Nthawi zambiri imagwiritsa ntchito chidziwitso cha ID ndipo imatha kutsitsa ndikubwezeretsa mawu olembedwa ku ID yoyamba ikafunika, koma fungulo liyenera kutetezedwa bwino.
- Kubisa kosasinthika: Ntchito ya hashi imagwiritsidwa ntchito pokonza deta, yomwe nthawi zambiri imagwiritsidwa ntchito pa ID.Sizingasinthidwe mwachindunji ndipo ubale wamapu uyenera kusungidwa.Kuphatikiza apo, chifukwa cha mawonekedwe a hashi, kugunda kwa data kumatha kuchitika.
- Homomorphic encryption: Ciphertext homomorphic algorithm imagwiritsidwa ntchito.Mawonekedwe ake ndiakuti zotsatira za ntchito ya ciphertext ndizofanana ndi zomwe zimachitika pambuyo polemba.Choncho, nthawi zambiri amagwiritsidwa ntchito pokonza magawo a manambala, koma sagwiritsidwa ntchito kwambiri pazifukwa zogwirira ntchito.
(3).System Technology
Tekinoloje yopondereza imachotsa kapena kuteteza zinthu zomwe sizikugwirizana ndi chitetezo chachinsinsi, koma sizizisindikiza.
- Masking: imatanthawuza njira yodziwika kwambiri yodetsa nkhawa kuti ibise mtengo wake, monga nambala yotsutsa, khadi ya ID yolembedwa ndi asterisk, kapena adilesi imadulidwa.
- Kuponderezedwa kwanuko: kumatanthawuza njira yochotseratu zikhalidwe zinazake (mizere), kuchotsa magawo osafunikira;
- Kuletsa kujambula: kumatanthawuza njira yochotsa zolemba zina (mizere), kuchotsa zolemba zosafunikira.
(4).Pseudonym Technology
Pseudomanning ndi njira yodziwikiratu yomwe imagwiritsa ntchito dzina lachinyengo m'malo mwa chizindikiritso chachindunji (kapena chizindikiritso china).Njira zachinyengo zimapanga zozindikiritsa zapadera pa mutu uliwonse wa chidziwitso, m'malo mwa zozindikiritsa zachindunji kapena zodziwika bwino.
- Imatha kupanga zinthu mwachisawawa payokha kuti zigwirizane ndi ID yoyambirira, kusunga tebulo lamapu, ndikuwongolera mosamalitsa mwayi wopezeka pamapu.
- Mutha kugwiritsanso ntchito kubisa kuti mupange ma pseudonyms, koma muyenera kusunga chinsinsi chachinsinsi bwino;
Ukadaulo uwu umagwiritsidwa ntchito kwambiri pazambiri za ogwiritsa ntchito odziyimira pawokha, monga OpenID muzochitika zotseguka, pomwe opanga osiyanasiyana amapeza Openids osiyanasiyana kwa wogwiritsa ntchito yemweyo.
(5).Generalization Techniques
Njira ya generalization imatanthawuza njira yosazindikiritsa yomwe imachepetsa kuchulukira kwa zinthu zomwe zasankhidwa mu seti ya data ndikupereka kufotokozera kwatsatanetsatane komanso kosamveka bwino kwa datayo.Ukadaulo wa generalization ndiwosavuta kugwiritsa ntchito ndipo utha kuteteza kutsimikizika kwa data yanthawi zonse.Amagwiritsidwa ntchito kwambiri pazinthu za data kapena malipoti a data.
- Kuzungulira: kumaphatikizapo kusankha maziko ozungulira pa zomwe mwasankha, monga zazamalamulo zakumwamba kapena pansi, kutulutsa zotsatira 100, 500, 1K, ndi 10K
- Njira zolembera zam'mwamba ndi zapansi: M'malo mwa mfundo zomwe zili pamwamba (kapena m'munsimu) poyambira ndikuyimira pamwamba (kapena pansi), kutulutsa zotsatira za "pamwamba pa X" kapena "pansi pa X"
(6).Ma Randomization Techniques
Monga mtundu wa njira yodziwikiratu, teknoloji ya randomisation imatanthawuza kusintha mtengo wa chikhalidwe kudzera mwa randomisation, kotero kuti mtengo pambuyo pa randomisation ndi wosiyana ndi mtengo weniweni weniweni.Izi zimachepetsa kuthekera kwa wowukira kuti apeze phindu kuchokera kuzinthu zina zomwe zili muzolemba zomwezo, koma zimakhudza kudalirika kwa deta yomwe imachokera, yomwe imakhala yodziwika ndi deta yoyesera kupanga.
Nthawi yotumiza: Sep-27-2022
