I-Biometrics Nokuphepha

Kwadalwa ngo 01.16
Kunezinhlaka ezimbili ezihlukene ezihilelekile enqenqemeni yesistimu ye-biometric – ukubhalisa nokufanisa.
Ukubhalisa. Njengoba kuboniswe kuMfanekiso 1, isampula ye-biometric yomuntu ithathwa ngesikhathi senqenqema yokubhalisa (isibonelo, kusetshenziswa inzwa yeminwe, imakrofoni yokuqashelwa kwesipikha, ikhamera yokuqashelwa kobuso, ikhamera yokuqashelwa kwamehlo). Izici eziyingqayizivele zibe sezikhishwa kusampula ye-biometric (isibonelo, isithombe) ukudala isifanekiso se-biometric somsebenzisi. Lesi sifanekiso se-biometric sigcinwa kusizindaba sedatha noma ekhadini le-ID elifundeka ngomshini ukuze lisetshenziswe kamuva ngesikhathi senqenqema yokufanisa.
Inqubo yokubhaliswa kwe-biometric: ukuthwebula, processing, ukugcina ithempulethi, kanye nokugcina idivayisi.
Ukufanisa. Isithombe 2 sibonisa inqubo yokufanisa i-biometric. Isampula ye-biometric sithathwa futhi. Izici ezihlukile zikhethwa kusampula ye-biometric ukudala isifanekiso se-biometric "esibukhoma" somsebenzisi. Lesi sifanekiso esisha siqhathaniswa nesifanekiso esigcinwe ngaphambili bese isikolo sokufanisa (ukufana) senombolo sikhiqizwa ngokusekelwe ekunqumeni izinto ezifanayo phakathi kwezifanekiso ezimbili. Abaklami besistimu banquma inani lomkhawulo lesi sikolo sokuqinisekisa ngokusekelwe ezidingweni zokuphepha nokulula zesistimu.
Ishadi lokuhamba kwe-biometric matching inenani lokuhambisana elingu-95%.
Izinhlelo zokuphepha ezisekelwe ku-Biometric zisebenzisa i-biometrics izinjongo eziyisisekelo ezimbili: ukuhlonza nokuqinisekisa.
Ukuqashelwa (ukuqhathanisa okukodwa-kuya-kokuningi noma 1:N) kunquma ukuthi umuntu ukhona yini emibuthanweni ebhalisiwe ngokufanisa isampula esiphila manje nezifanekiso zonke ezilondoloziwe ohlelweni. Ukuqashelwa kungaqinisekisa ukuthi umuntu akabhaliswanga ngegama elihlukile noma akasohlu olungaphambili lwabantu abavinjelwe. I-biometric yomuntu okucatshangelwa ukubhaliswa kwayo kufanele iqhathaniswe nawo wonke ama-biometrics alondoloziwe. Kwezinye izicelo zokuqinisekisa, inqubo yokuqashelwa kwe-biometric isetshenziswa ngesikhathi sokubhaliswa ukuqinisekisa ukuthi umuntu akabhaliswanga kakade.
Ukuqinisekisa (ukuqhathanisa okukodwa kwe-kudwa noma 1:1) kunquma ukuthi isibonelo se-biometric esiphila sivumelana yini nerekhodi elithile elibhalisiwe. Lokhu kufuna ukuthi kube "nesimangalo" sobunikazi ngumuntu ofuna ukuqinisekiswa ukuze kufinyelelwe kurekhodi elithile elibhalisiwe. Isibonelo kungaba ukwethulwa kwekhadi elihlakaniphile kanye nokuqhathanisa isibonelo se-biometric esiphila nesibonelo esibhalisiwe esigcinwe kumemori yekhadi elihlakaniphile. Esinye isibonelo kungaba ukufakwa kwegama lomsebenzisi noma inombolo ye-ID ezokhombisa kurekhodi elibhalisiwe kudathabhesi.
Ukukhethwa kobuchwepheshe obufanele be-biometric kuzoncika ezicini eziningana ezithinta uhlelo lokusebenza, okubandakanya imvelo lapho inqubo yokuhlonza noma yokuqinisekisa yenziwa khona, iphrofayela yomsebenzisi, izidingo zokufanisa ukunemba nokukhiqiza, izindleko zamandla ezinhlelo kanye namakhono, kanye nezindaba zamasiko ezingathinta ukwamukelwa ngabasebenzisi. Ithebula libonisa ukuqhathaniswa kobuchwepheshe obuhlukahlukene be-biometric, nokusebenza kwawo okulinganiselwe ngokumelene nezindlela eziningana.
Ithebula le-biometric identifiers eliqhathanisa ubuso, umunwe, isandla, iris, isiginesha, imithambo, kanye nezwi.
Isici esibalulekile ekukhethweni kobuchwepheshe obufanele be-biometric ukunemba kwabo. Lapho isibonelo se-biometric esiphila manje siqhathaniswa nesibonelo se-biometric esigciniwe (esicelo sokuqinisekisa), isikolo sokufana sisetshenziselwa ukuqinisekisa noma ukwenqaba ubunikazi bomsebenzisi. Abaklami besistimu babeka umkhawulo (isinqumo sokufana noma sokungafani) kulokhu skolo senombolo ukuze bavumelane nezinga elifunwayo lokusebenza kokufanisa kwesistimu, njengoba kulinganiswa yi-False Acceptance Rate (FAR) ne-False Rejection Rate (FRR). I-False Acceptance Rate ikhombisa ukuthi kungenzeka yini ukuthi uhlelo lwe-biometric luqinisekise umuntu ngokungafanele noma lwamukele umkhohlisi. I-False Rejection Rate ikhombisa ukuthi kungenzeka yini ukuthi uhlelo lwe-biometric lwenqabe umuntu olungile. Abaphathi besistimu ye-biometric bazolungisa ukuzwela kwesistimu ku-FAR ne-FRR ukuze bafinyelele ezingeni elifunwayo lokusebenza kokufanisa okusekela izidingo zokuphepha kwesistimu (isibonelo, endaweni ephephile kakhulu, ukulungisa ukuze kutholwe i-FAR ephansi nokubekezelela i-FRR ephezulu; endaweni elula kakhulu, ukulungisa ukuze kutholwe i-FAR ephezulu ne-FRR ephansi).
Ezinye izinkinga zokunemba nokusebenziseka ezibekwa ukusetshenziswa kwendlela eyodwa ye-biometric zinganqotshwa ngokusebenzisa izindlela eziningi ze-biometric. I-multi-modal biometrics ithuthukisa ukunemba okuphelele kokufanisa ngokusebenzisa izilinganiso eziningi nezizimele ze-biometric. Ngokwesibonelo, isikolo sokufanisa esivela ekulinganisweni kokuphrinta komunwe singahlanganiswa ngokwezibalo "nokulinganisa okuzimele kwephethini yomthambo esandleni ukuze kuvezwe izinga eliphezulu lokwethembeka ekuqaphelweni komuntu. Ngaphezu kwalokho, i-multi-modal biometrics inganikeza isixazululo kulabo bantu abangakwazi ukwethula isampula ye-biometric efanele kwenye indlela. Isibonelo kungaba ukunikeza inketho yokwethula umunwe noma amehlo ukuze kuqinisekiswe. Umuntu onamaphethini omunwe angacacile ngenxa yobudala, umsebenzi, noma isimo sezempilo angathola ukukhetha ukubhalisa nokusebenzisa amehlo njengendlela yakhe ye-biometric ayikhethayo. Uma izinzwa zombili zikhona, umsebenzisi angasebenzisa noma iyiphi indlela afanelekayo kuyo. Kulesi simo, akukho ukuhlanganiswa kwezilinganiso ze-biometric ezizimele. Njengoba kubonakala kuMfanekiso 3, izinhlelo ze-multi-biometric zingafaka ulwazi oluvela ezindleleni eziningi, izikhathi, ama-algorithm, izinzwa, izampula, noma noma yikuphi ukuhlanganiswa kwezinhlanu. Kungenzeka ukuthi izinhlelo ezinjalo zingafaka neminye imithombo yolwazi, okubandakanya ulwazi oluphathelene nobuhlanga noma olusekelwe emibhalweni yokuhamba.
Isithombe semithombo eminingi ye-biometric: amafayela, ama-sensors, imizimba, amehlo, kanye nezinhlelo.
I-Biometrics nezokuphepha kube yingxenye ebalulekile yokuzisebenzela, futhi iHuabiao Technology ihlale inamathele ekuvikelekeni njengomgomo wayo oyinhloko, ihlinzeka abasebenzisi ngezinsizakalo eziphephile neziphumelelayo. Ngeminye imininingwane mayelana nenkampani nokunikezwa kwayo, vakashela ku-Mayelana Nathi ikhasi noma uxhumane nge-Ukusekela ikhasi.
Umthombo:www.smartcardalliance.org, 2011 - irisid.com

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