Zviri Mukati[Viga][Ratidza]
Munyika yedhijitari, kune akati wandei matanho apo mapato echitatu anogona kuwana mutengi wako kana data rebhizinesi. Ruzivo rwakadaro harugone kubviswa nyore kubva mumishumo kana mushandisi mharidzo. Nenzira yakafanana, haugone kungogovera iyo data pachayo.
Dhata masking ndiyo yakakosha kuchengetedza mhinduro inotsiva iyo yakaratidzwa data ine fictional data uchichengeta iyo data yechokwadi yakachengeteka mumamiriro ezvinhu aya.
Dhata masking itsika yekushandura data rakavanzika zvekuti rinogona kushandiswa kune chinangwa chayo asi harigone kushandiswa kuona vanhu chaivo.
Data rinonzwisisika rinosanganisira mazita, kero, uye nhamba dzekuchengetedza magariro zvinotsiviwa neruzivo rwunonzwisisika asi rwenhema. Nenzira iyi, kunyangwe iyo data yakabiwa, iyo yakakosha ruzivo inodzivirirwa.
Mune ino positi, isu tichanyatso tarisa iyo yepamusoro gumi yedhata masking maturusi anowanikwa mumusika.
Chii chinonzi Data Masking?
Data masking inzira yekuvanza ruzivo rwakavanzika nekuitsiva neruzivo rwekunyepedzera, senge nhamba dzekadhi rechikwereti, mapassword, kana mamwe maitiro ekuzvizivisa.
Iri zano rinobvumidza kushandiswa kwe data rinomiririra kusimudzira, kuyedza, kana kudzidziswa uku uchivimbisa kuti data rakavandika rinochengetwa rakavanzika kunyangwe richigoverwa nemamwe mapato.
Sensitive data inogona kuvharika uchishandisa akasiyana matekiniki, anosanganisira tokenization, kutsiva, encryption, uye shuffling. Nepo shuffling ichirongedza kukosha kweiyo data, kutsiva kunotsiva iyo chaiyo data nemanyepo maitiro.
Nekune rimwe divi, encryption inovharidzira data nekuishandura kuita ciphertext inoda kiyi yedecryption kuti igadzirwe kuitira kuburitsa pachena data rekutanga. Tokenization inosanganisira kuchengeta iyo yekutanga fomati yedata inonzwisisika uchitsiva ma tokeni anongogadzirwa.
Chinangwa che data masking ndechekugadzira mhinduro inoshanda iyo isina ruzivo rwakadzama asi inopa duplicate yechimiro. Kana data chaiyo isingakodzeri, izvi zvinonyanya kubatsira pakudzidziswa kwemushandisi, demos yechigadzirwa, uye kuongororwa kwesoftware.
Sei data masking yakakosha zvakadaro?
Data masking inoshandiswa neakangwara uye anonyanya kuita masangano nekuda kwezvikonzero zvakati:
- Kubvisa mukana wekurasikirwa nedata kana kubira paunenge uchiisa data kune gore.
- Kugadzirisa nyaya dzakakosha dzekuchengetedza, senge data exfiltration, kutyisidzira kwemukati, maakaundi akakanganiswa, uye kushamwaridzana kusina kuchengetedzwa nekunze masisitimu.
- Kudzivirira vakwikwidzi kubva pakuwana zvirongwa zvekutengesa zvekambani yako, zvinosanganisira purofiti, huwandu hwevashandisi, uye zvimwe zvinhu.
- Kukugonesa kudzivirira kushandiswa kusingatenderwi kana kusiri iko kwevatengi data nevashandi, makondirakiti akazvimirira, kana vatengesi.
- Kubvumidza kushandiswa kwemahara kwekutengesa kwe data rakavanzwa nevanodzidzira basa, vagadziri, vagadziri, vagadziri vemukati, uye veruzhinji.
- Dhata sanitization inoshandisa data masking kutsiva iyo yekutanga kukosha pane yekuchengetera svikiro, nepo yakajairwa kudzima faira kuchiri kusiya dhata kumashure.
Data Masking Zvishandiso
1. Delphix
Delphix is state-of-the-art software inokwanisa kukurumidza kuona nekuvanza data rakadzama kubva kune akati wandei, kusanganisira hukama dhatabhesi uye mafaera.
Mazita evatengi, kero dzeemail, uye nhamba dzekadhi rechikwereti hazvinei newe nekuti Delphix inogona kungoona anopfuura makumi matatu emhando dzakasiyana dzeruzivo.
Yakasiyana-siyana yemhando yedata, kusanganisira yakarongeka uye isina kurongeka data, inogona kuvharika uchishandisa iyi application. Delphix inoshandisa nzira dzakasiyana siyana dzekuvanza data, kusanganisira hashing, kutsiva, uye shuffling.
Iine anopfuura makumi mashanu ehunyanzvi ekutaura, Delphix inosanganisira yakakura raibhurari ye pre-yakavakwa profiles seti. Kumhanyisa masking algorithms hazvidi kuti iwe uve nyanzvi yekuronga, uye Delphix inogona kuburitsa hunhu chaihwo uku uchichengeta referensi yekutendeseka mukati uye mukati medata rako masosi.
Iyo software zvakare inongogadziriswa kana iwe uchida kugadzira algorithms nyowani. Yako yakafukidzwa data icharamba ichishanda zvisina mhosva, ichikugonesa iwe kuishandisa kusimudzira, kuyedza, uye kuongorora zvinodiwa.
Data tokenization uye isingadzoreki masking mhinduro zvinopihwa neDelphix kuchengetedza kuvanzika kwedata uye kuchengetedzeka kwebhizinesi rako kunofanirwa kutevedzera zviyero nemitemo seGDPR, HIPAA, kana CCPA. Njodzi dzinogona kubviswa nekutsanangura nekushandisa yunifomu masking maitiro pane ese asiri ekugadzira marongero.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
2. IBM InfoSphere Optim Data Privacy
Iyo IBM InfoSphere Optim Data Privacy mhinduro inogonesa vashandisi kutsiva data rakadzama neine mamiriro akakodzera uye echokwadi (asi engano) data nenzira dzakasiyana.
Iyo tekinoroji inoita kuti ive yakatwasuka kumabhizinesi kuwana data rakavanzika uye kuifukidza sezvinodiwa mukati medhatabhesi, matura, gore, uye makuru data mamiriro.
Kubata uye kuvharika kweruzivo rwakadzama (PII nedzimwe data rakavanzika) rinoitwa nyore mune zvisiri zvekugadzira zvinosanganisira kusimudzira, kuyedzwa, uye vimbiso yemhando yekutenda kune IBM InfoSphere Optim Data Privacy.
InfoSphere inopa kuchengetedzeka kwedata uye kuvanzika kunodiwa neindasitiri yeBFSI, kunyanya mune akawanda-vatengesi kusimudzira / kutsigira ecosystem. Icho chishandiso chakakwana chekuchengetedza kuvanzika kwedata uye nharaunda.
Kumisikidza kudhirowa kwedata kubva mukugadzira dhatabhesi uye masking nzira, hapana coding inodiwa. Shanduko inoitika nekukurumidza mugero rakachengeteka. IBM inovimbisa kuvandudzwa mukutevedzera data, manejimendi enjodzi, uye mashandiro ekuita.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
3. K2View
K2View inogona kuve yakakunakira sarudzo kana iwe uchitsvaga yakasimba data masking chishandiso chinogona kuchengetedza zvine hungwaru data rako.
Izvo zvakagadzirirwa kuita kuti data masking ive nyore nekudzikisa mutengo wekutumira uye nguva uchibvisawo bhizinesi-nhanho matambudziko neayo chigadzirwa che data.
K2View inopa kuchengetedzeka kwakasimba kwePII data uye inochengetedza kuwirirana kwedata rakafukidzwa nekusazivikanwa ine hanya yemunhu data mukufamba.
Pamusoro pezvo, inogadzirwa kuti ikubatsire mukuomerera kune akati wandei ekuchengetedza data, senge GDPR, CCPA/CPRA, HIPAA, LGPD, uye PCI DSS.
K2View ine data cataloging uye auto-discovery kugona kunoita kuti zvive nyore kumepu uye kurongedza data rakadzama. Uyezve, iwe unogona kuitisa dhatabhesi faira uye metadata kutsvaga pane granular level.
Iwe une rusununguko rwekuvanza data rako nenzira inonyanya kushanda kune bhizinesi rako nekuda kwemazana ekunze-kwe-the-bhokisi nzira dze masking dziripo, kusanganisira kutsiva, randomizing, shuffling, switching, nulling-out, and redaction.
Pamusoro pezvo, K2View inotsigira kubatanidzwa kusina musono neakasiyana siyana matekinoroji kana data masosi, angave ari anotambirwa munharaunda kana mugore. Kuti uvanze data nereferensi yekutendeseka, unogona kubatanidza iyi mhinduro kune ehukama dhatabhesi, legacy system, NoSQL, XML zvinyorwa, meseji mitsara, uye akafuratira mafaera.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
4. Oracle Data masking uye subsetting
Oracle Data Masking uye Subsetting chishandiso chinoshanda chinoita kuti makambani adzikise njodzi yekutyorwa kwedata uku achichengetedza mhando yedata kune isiri-yekugadzira marongero. Mhinduro yacho inosanganisira akati wandei akavakirwa-mukati data masking matekiniki, anosanganisira redaction, kutsiva, uye kukwenya, kuviga data rakadzama nenzira inoita kuti irambe ichishandiswa asi ichivharidzira kuzivikanwa kwayo.
Nekusimudzira, kuyedza, uye zvinangwa zvekuongorora, Oracle Data Masking uye Subsetting inopawo subsetting kugona kuburitsa mamwe anodzoreka makopi ekugadzira data.
Nepo masking uye subsetting data, inogona kuchengetedza referensi kuvimbika, hukama hwakaoma, uye kutsamira. Databases, mafaera, uye maapplication ari pa-nzvimbo kana mugore anogona kushandiswa nemhinduro. Ruzivo rwepachivande rweDatabhesi uye vana varo zvinongozivikanwa nechirongwa ichi.
Iyo inochengetedza raibhurari yepakati yemasiki mafomati, iyo inopa yakagadzirira-kushandisa-masiki mafomu uye inopa vashandisi nzira dzakawanda dzekuvanza chero data rakapihwa. Nekuvanza data kubva kumakesi akasiyana ekushandisa pasi peakasiyana marongero, Oracle inopa yakakwana shanduko nzira.
Zvakakodzera kumabhizinesi anofanirwa kutevedzera mitemo inodzora kuvanzika kwedata, seGDPR, CCPA/CPRA, HIPAA, nemamwe. Mazita, kero, nhamba dzenhare, maemail, nhamba dzekadhi rechikwereti, uye ruzivo rwehutano zvese zvinogona kuvanzwa nemhinduro.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
5. Informatica Persistent Data Masking
Informatica Persistent Data Masking ndeye yakazara data masking mhinduro inobvumira mabhizinesi kuchengetedza zvakachengetedzeka data data uchiigovana nevanobata mukati nekunze.
Iwo akaomesesa algorithms anoshandiswa mumhinduro iyi anogonesa kuchengetedzwa kweruzivo rwakadzama uchishandisa akasiyana matipi ekuisa masking, senge fomati-kuchengetedza uye kukosha-kuchengetedza masking. Iyo tekinoroji, iyo inogona kuvhara data munguva chaiyo kana mumabhechi, inochengetedza data rakadzama panguva yekufambisa uye mubatch mode.
Databases, mafaera, uye mainframes angori mashoma enzvimbo kwaanogona kuvanza data. Kushandiswa kwechirongwa ichi kunogonesa kuvanza kwedata pamapuratifomu akati wandei, anosanganisira Oracle, IBM DB2, Microsoft SQL Server, nemamwe.
Mhinduro yacho yakanakira mamwe mabhizinesi anochinjisa data rawo kune gore nekuti zvakare ine data masking kugona munzvimbo dzemakore. Iyo mhinduro yakasimba yekubika uye yekuongorora maficha regai vatengi vatarise uye vatarise zvese masking chiitiko.
Mitemo yakasiyana, yakadai seGDPR, HIPAA, uye PCI-DSS, inogona kuratidzwa kuti yakatevedzwa nekushandisa mishumo inogadzirwa nemhinduro. Iyo inovanza chidimbu chega chega cheruzivo rwunozivikanwa kubva muhuwandu hukuru hwe data yakaunganidzwa kubva kune akawanda masosi uye dhatabhesi, sevashandisi, nzvimbo, mazuva ekuzvarwa, uye mabasa.
Databases, maapplication, uye mainframes ese anogona kubatanidzwa zvakanyanya nemhinduro. Uyezve, inoderedza mukana wekurasikirwa nedata kana kushandisa zvisizvo data.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
6. IRI FieldShield
IRI FieldShield ine simba data masking system inopa yekucheka-kumucheto chengetedzo ye data inonzwisisika. Iyo yakazara seti yezvimiro uye masking maitiro echirongwa anogonesa vashandisi kukurumidza kuvhara data kubva kwakasiyana siyana masosi, kusanganisira ane hukama dhatabhesi, flat mafaira, uye mainframe masisitimu. Inopawo vashandisi sarudzo yegore-yakavakirwa kana pane-nzvimbo yedata masking.
FieldShield inowana otomatiki uye inoisa mumapoka zvinhu zvine hunyoro mumadatabase, mafaera, uye mamwe masosi uchishandisa inoveli data categorization maitiro. Kana data yaiswa muchikamu, inogona kuvanzwa uchishandisa akati wandei matekiniki, kusanganisira encryption, kutsiva, uye redaction.
Pamusoro pezvo, akasiyana siyana emhando dzedata, kusanganisira alphanumeric, manhamba, uye Unicode, anotsigirwa. Iyo zvakare inoita shuwa kuti masked data inochengeta referensi kuenderana nemamwe data ane hukama, kuchengetedza kukosha kweiyo data.
Inopawo huwandu hwesarudzo dzekugadzirisa data, zvichibvumira kugadzirwa kwediki data seti yekuyedza nekusimudzira.
Kubatanidzwa nezvimwe zvigadzirwa zveIRI seIRI CoSort uye IRI Voracity inotsigirwawo neFieldShield. Zvishandiso izvi zvinopa mamwe maficha pachikuva chimwe chete, kusanganisira kubatanidzwa kwedata, mhando yedata, uye masking data.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
6. Salesforce Data mask
Salesforce Data Mask ine simba data masking tekinoroji inobatsira mabhizinesi kuchengetedza ruzivo rwavo rwakadzama uye kuomerera kune akasiyana mitemo yekudzivirira data. Mhando dzakasiyana-siyana dzemaskking sarudzo dziripo papuratifomu ino, kusanganisira inochinja data masking, static data masking, uye yakasarudzika data masking.
Sales Cloud, Cloud Sevhisi, uye Yekushambadzira Cloud data rinozivikanwa uye rakavharwa neSalesforce Data Mask vachishandisa muchina kudzidza algorithms.
Iyo tekinoroji inopawo yakakwana dashboard inoita kuti vatengi vaone marekodhi ekuongorora uye kufambira mberi kwavo masking. Mitemo yakasiyana-siyana yekudzivirira data inosanganisira GDPR, CCPA, uye HIPAA, zvakare ine pre-yakavakwa yekutevedzera matemplate.
Salesforce Data Mask inoshanda pamwe chete nezvimwe zvigadzirwa zveSalesforce seShield uye Identity kuti ipe yakakwana yekudzivirira data mhinduro. Pamusoro pezvo, Salesforce Data Mask inopa yakakwira dhigirii yekumisikidza kuchinjika uye inogona kumisikidzwa kugutsa izvo zvinodikanwa zvekuchengetedzwa kwedata kwemasangano akasiyana.
Mhando dze data dzinoshandiswa zvakanyanya senge tsika uye zvakajairwa zvinhu, minda, zvakabatanidzwa, uye zvinyorwa zvese zvinotsigirwa masking. Inopawo akawanda masking nzira dzinosanganisira kutsiva, redaction, tokenization, uye encryption kuvimbisa kuti data rakavanzwa zvakabudirira uchichengetedza kuvimbika kwayo.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
7. Immuta
Immuta inogona kuve yakanakisa sarudzo yezvirambidzo zvekuvanzika uye ine simba data masking. Iyo inogadzirisa iyo data panguva yekubvunza kuvanza zvakakosha zvakakosha pasina kushandura iyo yekutanga data.
Iwe unogona kutsanangura hunhu-hwakavakirwa yekuwana yekudzora mutemo mukuchengetedza kwayo uye kuvanzika manejimendi suite. Iwe une sarudzo yekushandisa kodhi kana mutauro wakajeka paunenge uchinyora mutauro wemitemo.
Pamusoro pezvo, iwe unogona kusarudza kubva kune anopfuura makumi matanhatu pre-yakavakwa chengetedzo uye zvakavanzika zvinodzora kuchengetedza data inonzwisisika. Izvi zvipingamupinyi zvinogona zvakare kushandiswa zvine simba panguva yekubvunza kune dzakasiyana siyana data masking matekiniki, anosanganisira kusazivikanwa, pseudonymization, minimization, uye obfuscation.
Iwe unogona kukurumidza kuwana iyo yakatenderwa data kubva kune chero kabhuku, BI chishandiso, kana workbench nekuda kweaya masimba masimba. Iwe unogona otomatiki miganho yekuwana paImmuta uchishandisa akasiyana maitiro, anosanganisira mushandisi wehuwandu, nguva-yakavakirwa windows, yakavakidzana sero data, uye referenzi tafura data.
Pamusoro pezvose, inoderedza mutoro weinjiniya uye inogonesa kupinda ipapo kune yakavharidzirwa data. Pamusoro pezvo, iyi software inodzikisira mukana wekutyorwa kwedata, inochengetedza mukurumbira wekambani yako, inogonesa kugovana data kwakachengeteka, uye inowedzera kubudirira kwechikwata.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
8. Chainsys DataZense
DataZense ndeye yakazara data masking mhinduro yakagadzirwa kuchengetedza yakavanzika ruzivo mune isiri-kugadzira, kusimudzira, uye kuyedza marongero. Makambani anogona kuvanza nyore PII nePHI data, kusanganisira ruzivo rwekadhi rechikwereti, mazita, kero, uye marekodhi ekurapa, neiyi tekinoroji.
Inogona kukurumidza kuchengetedza nguva uye kuderedza kukanganisa kwevanhu nekuona otomatiki uye masking data. Nzira dzekuvharisa dzinopihwa nechishandiso ichi dzinosanganisira tokenization, encryption, shuffling, kutsiva, uye masking. Inogona kuchengetedza kutendeseka uye data linkages nekuda kweiyo kunze-kwe-iyo-bhokisi algorithms.
Pamusoro pezvo, zvinokutendera kuti ugadzire yakasarudzika masiki mitemo uye marongero, ichivimbisa kuti data rakavanzika harizivikanwe maererano nezvaunoda.
Inopawo akati wandei sarudzo dzekugadzirisa uye nzira dzekuongorora dzekuteedzera uye kutarisa. Iwe unogona kuwana iyi gore-yakavakirwa papuratifomu chero nguva uye chero kwaunosarudza.
Pamusoro pezvo, inotsigira iyo GDPR, CCPA, OIOO, uye mimwe mitemo yekuvanzika. Mahombe data mapuratifomu, ehukama dhatabhesi, akafuratira mafaera, makore masevhisi, uye mamwe masosi data uye matekinoroji anogona kubatanidzwa nedataZense.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
9. NextLabs
Nextlabs Data Masking, ine simba data security solution, inoita kuti mabhizinesi achengetedze data rakadzama uku achitevedzera zvinodiwa nemutemo. Iwo akavanzika data zvikamu izvo chirongwa ichi chinoita kuti vashandisi vaone nekuvanza zvinosanganisira ruzivo rwekadhi rechikwereti, nhamba dzekuchengetedza magariro, uye kero dzeemail, kungotaura zvishoma.
Inopa masking ye data isina kurongeka mukuwedzera kune yakarongeka data.
NeNexlabs Data Masking, unogona kuita masking marongero anogona kushandiswa neakasiyana madhata masosi, kusanganisira mafaera, dhatabhesi, uye software zvirongwa.
Kuchengetedza data rakavanzika, chishandiso chinoshandisa nzira dzakasiyana-siyana dzekuvharira, kusanganisira encryption, redaction, substituting, uye shuffling. Nerubatsiro rweNextlabs Data Masking, unogona kubata uye kuramba wakatarisa pane yako data masking marongero nekuda kwekutarisa kwepakati kwese ako data masosi.
Iyo sisitimu inogonesa kuongororwa uye kushuma kwekushandiswa kwedata uye kuwana.
Kudzivirirwa kwedata kurasikirwa (DLP) uye kuzivikanwa uye kuwana manejimendi (IAM) zvigadzirwa, pamwe nedzimwe mhinduro dzekuchengetedza, zvese zviri zviviri zvakabatanidzwa neNextlabs Data Masking. Nekubatanidza masisitimu aya, masangano anokwanisa kugadzira hurongwa hwekuchengetedza data hwakakwana hunochengetedza chikamu chimwe nechimwe chenzvimbo yavo yedata.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
10 HusHus
Kutsvaga mhinduro yakavanzika yekukubatsira iwe nedata masking kuti iwe ugone kutevedzera zvinodzorwa uye zveveruzhinji zvakavanzika zviyero? Hush-Hush ndiyo yakanakira sarudzo. Iwe une Hush-Hush mhinduro, zvakadaro, kuti ikubatsire mukuvanza PII data.
Uchishandisa iyi software, unogona kukurumidza kuwana ruzivo rwakadzama mune dhatabhesi yekambani yako uye kuironga muzvikamu zvekusazivikanwa. Hush-Hush inoenderana zvizere neGDPR, HIPAA/HITECH, CCPA, uye GLBA mirau kana zvasvika pakuvharisa data.
Inoshandisa yemitemo-yakavakirwa zvikamu zvekugadzirisa kwakaringana uye yakachengeteka data kusazivikanwa, ichipa yakagadzirira-kushandisa-mhinduro kuvanza yakananga uye isina kunanga kuzivikanwa uchishandisa yakafanotemerwa uye yepasirese nzira.
Hush-Hush inochinjika uye inogona kubatanidzwa neyako SQL server SSIS, Biztalk, uye kodhi uchishandisa API ungave uri kushanda-panzvimbo kana mugore. Iyo sisitimu inogadzira mishumo yekuongorora yekuongorora kuti ione kutevedza kwemutemo neGDPR, CCPA, uye HITECH, uye iwe unogona kuronga zviitiko zvekusazivikanwa kwedata kana kuzviita sezvinodiwa.
Pricing
Ndokumbira ubate mutengesi nezvemitengo yayo.
mhedziso
Kupfupisa, kuvharisa data inzira yakakosha kumafemu emazuva ano kuchengetedza data rakadzama kubva pakuwanikwa kusingatenderwe. Nekushandisa data masking matekiniki, mabhizinesi anogona kuchengetedza yavo yakakosha data pasina kukanganisa maitiro avo enguva dzose.
Mabhizinesi anogona kusarudza mhinduro yakanakisa zvichienderana nezvavanoda zvakasiyana, kusanganisira huwandu hwekuchengetedzwa kwedata kunodiwa, marudzi edata masosi anoshandiswa, uye zvinodikanwa zvekuteedzera, nekuda kwemusika wakasiyana-siyana wedzimwe nzira.
José Rodrigues Gonçalves Filho
Yako post yakaenda kupfuura zvandaitsvaga - chishandiso chekusaziva zita mufaira rePDF...
Kuverenga kwangu LGPD nhasi ndeyekuti, nepo mutemo uchidzivirira mugari, unoremedza veruzhinji zvakanyanya. Mupfungwa iyi, chishandiso chinosvikika (mupfungwa yakafara yezwi) chinodiwa apo masangano anoita maitiro ekutonga awanikwe kune vanonyorera!