{"id":12101,"date":"2024-03-11T10:00:43","date_gmt":"2024-03-11T07:00:43","guid":{"rendered":"https:\/\/www.kaspersky.com.tr\/blog\/?p=12101"},"modified":"2024-03-11T11:12:28","modified_gmt":"2024-03-11T08:12:28","slug":"ambient-light-sensor-privacy","status":"publish","type":"post","link":"https:\/\/www.kaspersky.com.tr\/blog\/ambient-light-sensor-privacy\/12101\/","title":{"rendered":"Bir casusluk arac\u0131 olarak ortam \u0131\u015f\u0131\u011f\u0131 sens\u00f6r\u00fc"},"content":{"rendered":"

Science Magazine<\/a>\u2018de Ocak ay\u0131 ortas\u0131nda yay\u0131nlanan bir makale, ortam \u0131\u015f\u0131\u011f\u0131 sens\u00f6r\u00fc arac\u0131l\u0131\u011f\u0131yla ak\u0131ll\u0131 telefon kullan\u0131c\u0131lar\u0131n\u0131 g\u00f6zetlemenin dikkate de\u011fer bir y\u00f6ntemini anlat\u0131yor. T\u00fcm ak\u0131ll\u0131 telefonlar ve tabletlerde ve hatta diz\u00fcst\u00fc bilgisayarlar ve TV\u2019lerde de bu bile\u015fen yerle\u015fik olarak bulunuyor. Ana g\u00f6revi, cihaz\u0131n bulundu\u011fu ortamdaki ortam \u0131\u015f\u0131\u011f\u0131 miktar\u0131n\u0131 alg\u0131lamak ve ekran\u0131n parlakl\u0131\u011f\u0131n\u0131 buna g\u00f6re de\u011fi\u015ftirmektir.<\/p>\n

Ancak \u00f6nce bir sald\u0131rgan\u0131n neden hedef cihaz\u0131n normal kameras\u0131 yerine g\u00f6r\u00fcnt\u00fc yakalamak i\u00e7in uygun olmayan bir ara\u00e7 kulland\u0131\u011f\u0131n\u0131 a\u00e7\u0131klamam\u0131z gerekiyor. Bunun nedeni, bu t\u00fcr \u201cuygun olmayan\u201d sens\u00f6rlerin genellikle tamamen korumas\u0131z olmas\u0131d\u0131r. Bir sald\u0131rgan\u0131n bir kullan\u0131c\u0131y\u0131 ak\u0131ll\u0131 telefonuna k\u00f6t\u00fc ama\u00e7l\u0131 bir program y\u00fcklemesi i\u00e7in kand\u0131rd\u0131\u011f\u0131n\u0131 d\u00fc\u015f\u00fcnelim. K\u00f6t\u00fc ama\u00e7l\u0131 yaz\u0131l\u0131m, mikrofon veya kamera gibi s\u0131k\u00e7a hedeflenen bile\u015fenlere eri\u015fim sa\u011flamak konusunda zorlanacakt\u0131r. Peki ya \u0131\u015f\u0131k sens\u00f6r\u00fcne? \u00c7ocuk oyunca\u011f\u0131.<\/p>\n

Ara\u015ft\u0131rmac\u0131lar, ortam \u0131\u015f\u0131\u011f\u0131 sens\u00f6r\u00fcn\u00fcn kamera yerine kullan\u0131labilece\u011fini kan\u0131tlad\u0131lar; \u00f6rne\u011fin, kullan\u0131c\u0131n\u0131n sanal klavyede PIN girerken elinin anl\u0131k g\u00f6r\u00fcnt\u00fcs\u00fcn\u00fc almak i\u00e7in. Teorik olarak, bu t\u00fcr verileri analiz ederek parolan\u0131n kendisini yeniden olu\u015fturmak m\u00fcmk\u00fcnd\u00fcr. Bu yaz\u0131da her \u015fey sade bir dille anlat\u0131l\u0131yor.<\/p>\n

I\u015f\u0131k sens\u00f6r\u00fcyle \"\u00e7ekim yapmak\".<\/a>

I\u015f\u0131k sens\u00f6r\u00fcyle \u201c\u00e7ekim yapmak\u201d. Kaynak<\/a><\/p><\/div>\n

I\u015f\u0131k sens\u00f6r\u00fc olduk\u00e7a ilkel bir teknolojidir. Asl\u0131nda ortam \u0131\u015f\u0131\u011f\u0131n\u0131n parlakl\u0131\u011f\u0131n\u0131 saniyede birka\u00e7 kez \u00f6l\u00e7en \u0131\u015f\u0131\u011fa duyarl\u0131 bir fotoseldir. Dijital kameralar da \u00e7ok benzer (daha k\u00fc\u00e7\u00fck de olsa) \u0131\u015f\u0131k sens\u00f6rleri kullan\u0131r, ancak bunlardan milyonlarca vard\u0131r. Lens bu fotosel matrisine bir g\u00f6r\u00fcnt\u00fc yans\u0131t\u0131r, her bir elementin parlakl\u0131\u011f\u0131 \u00f6l\u00e7\u00fcl\u00fcr ve sonu\u00e7 dijital bir foto\u011fraf olur. B\u00f6ylelikle, bir \u0131\u015f\u0131k sens\u00f6r\u00fcn\u00fcn dijital foto\u011fraf makinelerinin en ilkeli oldu\u011funu s\u00f6yleyebiliriz: \u00e7\u00f6z\u00fcn\u00fcrl\u00fc\u011f\u00fc tam olarak bir pikseldir. B\u00f6yle ilkel bir teknoloji etraf\u0131nda olup bitenleri nas\u0131l yakalayabilir ki?<\/p>\n

Ara\u015ft\u0131rmac\u0131lar, 19. y\u00fczy\u0131l\u0131n ortalar\u0131nda form\u00fcle edilen Helmholtz kar\u015f\u0131l\u0131kl\u0131l\u0131k ilkesini<\/a> kulland\u0131lar. Bu ilke, \u00f6rne\u011fin bilgisayar grafiklerinde yayg\u0131n olarak kullan\u0131lmakta ve hesaplamalar\u0131 b\u00fcy\u00fck \u00f6l\u00e7\u00fcde basitle\u015ftirmektedir. Bu ilke, 2005 y\u0131l\u0131nda \u00f6nerilen<\/a> ikili foto\u011fraf\u00e7\u0131l\u0131k y\u00f6nteminin temelini olu\u015fturmu\u015ftur. A\u00e7\u0131klamaya yard\u0131mc\u0131 olmas\u0131 a\u00e7\u0131s\u0131ndan bu makaleden bir \u00f6rnek sunal\u0131m:<\/p>\n

\"Solda<\/a>

Solda nesnenin ger\u00e7ek bir foto\u011fraf\u0131 var. Sa\u011fda da \u0131\u015f\u0131k kayna\u011f\u0131n\u0131n bak\u0131\u015f a\u00e7\u0131s\u0131ndan hesaplanan bir g\u00f6r\u00fcnt\u00fc var. Kaynak<\/a><\/p><\/div>\n

Bir masan\u0131n \u00fczerindeki nesnelerin foto\u011fraf\u0131n\u0131 \u00e7ekti\u011finizi d\u00fc\u015f\u00fcn\u00fcn. Nesnelerin \u00fczerine bir \u0131\u015f\u0131k kayna\u011f\u0131 parlar, yans\u0131yan \u0131\u015f\u0131k kamera merce\u011fine \u00e7arpar ve sonu\u00e7 bir foto\u011fraf ortaya \u00e7\u0131kar. Burada s\u0131ra d\u0131\u015f\u0131 bir \u015fey yok. Yukar\u0131daki resimde, soldaki g\u00f6r\u00fcnt\u00fc tam olarak budur \u2013 normal bir foto\u011fraf. Daha sonra, ara\u015ft\u0131rmac\u0131lar b\u00fcy\u00fck \u00f6l\u00e7\u00fcde basitle\u015ftirilmi\u015f terimlerle, lamban\u0131n parlakl\u0131\u011f\u0131n\u0131 de\u011fi\u015ftirmeye ve ayd\u0131nlatmadaki de\u011fi\u015fiklikleri kaydetmeye ba\u015flad\u0131lar. Sonu\u00e7 olarak, sa\u011fdaki g\u00f6r\u00fcnt\u00fcy\u00fc yeniden olu\u015fturmak i\u00e7in yeterli bilgi toplad\u0131lar \u2013 sanki lamban\u0131n bak\u0131\u015f a\u00e7\u0131s\u0131ndan al\u0131nm\u0131\u015f gibi. Bu konumda kamera yok ve hi\u00e7bir zaman da olmad\u0131, ancak \u00f6l\u00e7\u00fcmlere dayanarak sahne ba\u015far\u0131yla yeniden olu\u015fturuldu.<\/p>\n

En ilginci de bu y\u00f6ntemin bir kameraya bile ihtiya\u00e7 duymamas\u0131. Basit bir fotorezist\u00f6r i\u015fi g\u00f6r\u00fcr\u2026 t\u0131pk\u0131 ortam \u0131\u015f\u0131\u011f\u0131 sens\u00f6r\u00fcnde oldu\u011fu gibi. Bir fotorezist\u00f6r (veya \u201ctek pikselli kamera\u201d) nesnelerden yans\u0131yan \u0131\u015f\u0131ktaki de\u011fi\u015fiklikleri \u00f6l\u00e7er ve bu veriler nesnelerin bir foto\u011fraf\u0131n\u0131 olu\u015fturmak i\u00e7in kullan\u0131l\u0131r. G\u00f6r\u00fcnt\u00fcn\u00fcn kalitesi d\u00fc\u015f\u00fck olacakt\u0131r ve say\u0131lar\u0131 y\u00fczlerce veya binlerce olan \u00e7ok say\u0131da \u00f6l\u00e7\u00fcm yap\u0131lmas\u0131 gerekecektir.<\/p>\n

\"Deney<\/a>

Deney d\u00fczene\u011fi: bir Samsung Galaxy View tablet ve bir manken eli. Kaynak<\/a><\/p><\/div>\n

\u00c7al\u0131\u015fmaya ve \u0131\u015f\u0131k sens\u00f6r\u00fcne geri d\u00f6nelim. Makalenin yazarlar\u0131 17 in\u00e7 ekrana sahip olduk\u00e7a b\u00fcy\u00fck bir Samsung Galaxy View tablet kulland\u0131lar. Tabletin ekran\u0131nda siyah ve beyaz dikd\u00f6rtgenlerden olu\u015fan \u00e7e\u015fitli desenler g\u00f6r\u00fcnt\u00fclendi. Bir manken, ekran klavyesine bir \u015feyler giren bir kullan\u0131c\u0131 rol\u00fcnde ekrana bakacak \u015fekilde konumland\u0131r\u0131ld\u0131. I\u015f\u0131k sens\u00f6r\u00fc parlakl\u0131ktaki de\u011fi\u015fiklikleri yakalad\u0131. Bunun gibi birka\u00e7 y\u00fcz \u00f6l\u00e7\u00fcmde, mankenin elinin bir g\u00f6r\u00fcnt\u00fcs\u00fc \u00fcretildi. Yani, yazarlar Helmholtz kar\u015f\u0131l\u0131kl\u0131l\u0131k ilkesini uygulayarak elin, ekran\u0131n bak\u0131\u015f a\u00e7\u0131s\u0131ndan \u00e7ekilmi\u015f gibi bir foto\u011fraf\u0131n\u0131 elde etmeyi ba\u015fard\u0131lar. Ara\u015ft\u0131rmac\u0131lar tablet ekran\u0131n\u0131 son derece d\u00fc\u015f\u00fck kaliteli bir kameraya d\u00f6n\u00fc\u015ft\u00fcrd\u00fcler.<\/p>\n

Tabletin \u00f6n\u00fcndeki ger\u00e7ek nesneler ile \u0131\u015f\u0131k sens\u00f6r\u00fcn\u00fcn yakalad\u0131klar\u0131n\u0131n kar\u015f\u0131la\u015ft\u0131rmas\u0131. <a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/www.science.org\/doi\/epdf\/10.1126\/sciadv.adj3608\" target=\"_blank\">Kaynak<\/a><\/a>

Tabletin \u00f6n\u00fcndeki ger\u00e7ek nesneler ile \u0131\u015f\u0131k sens\u00f6r\u00fcn\u00fcn yakalad\u0131klar\u0131n\u0131n kar\u015f\u0131la\u015ft\u0131rmas\u0131.<\/p><\/div>\n

Do\u011fru, \u00e7ok net bir g\u00f6r\u00fcnt\u00fc de\u011fil. Sol \u00fcstteki resim neyin yakalanmas\u0131 gerekti\u011fini g\u00f6steriyor: birinde mankenin a\u00e7\u0131k avu\u00e7 i\u00e7i; di\u011ferinde ise \u201ckullan\u0131c\u0131n\u0131n\u201d ekrandaki bir \u015feye dokunurken nas\u0131l g\u00f6r\u00fcnd\u00fc\u011f\u00fc. Ortadaki g\u00f6r\u00fcnt\u00fcler 32\u00d732 piksel \u00e7\u00f6z\u00fcn\u00fcrl\u00fckte yeniden olu\u015fturulmu\u015f bir \u201cfoto\u011fraf\u201d olup, neredeyse hi\u00e7bir \u015fey g\u00f6r\u00fcnmemektedir \u2013 verilerde \u00e7ok fazla kumlanma vard\u0131r. Ancak makine \u00f6\u011frenimi algoritmalar\u0131n\u0131n yard\u0131m\u0131yla kumlanma filtrelenerek bir elin konumunu di\u011ferinden ay\u0131rt edebildi\u011fimiz sa\u011fdaki g\u00f6r\u00fcnt\u00fcler elde edildi. Makalenin yazarlar\u0131, insanlar\u0131n tabletin dokunmatik ekran\u0131n\u0131 kullan\u0131rken yapt\u0131klar\u0131 tipik hareketlere ba\u015fka \u00f6rnekler de veriyor. Daha do\u011frusu, onlar\u0131 nas\u0131l \u201cfoto\u011fraflamay\u0131\u201d ba\u015fard\u0131klar\u0131na dair \u00f6rnekler:<\/p>\n

\"Bir<\/a>

Bir \u0131\u015f\u0131k sens\u00f6r\u00fc kullanarak \u00e7e\u015fitli el pozisyonlar\u0131n\u0131 yakalama. Kaynak<\/a><\/p><\/div>\n

Peki bu y\u00f6ntemi pratikte uygulayabilir miyiz? Kullan\u0131c\u0131n\u0131n bir tablet veya ak\u0131ll\u0131 telefonun dokunmatik ekran\u0131yla nas\u0131l etkile\u015fime girdi\u011fini izlemek m\u00fcmk\u00fcn m\u00fc? Ekran klavyesine metin giri\u015fi yaparken? Kredi kart\u0131 bilgilerini girerlerken? Uygulamalar\u0131 a\u00e7arlarken? Neyse ki bu o kadar basit de\u011fil. Yukar\u0131daki resimde yer alan \u201cfoto\u011fraflar\u0131n\u201d \u00fczerindeki ba\u015fl\u0131klara dikkat edin. Bunlar y\u00f6ntemin ne kadar yava\u015f \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 a\u00e7\u0131k\u00e7a g\u00f6steriyor. En iyi senaryoda, ara\u015ft\u0131rmac\u0131lar \u00fc\u00e7 dakikadan biraz fazla bir s\u00fcrede elin bir \u201cfoto\u011fraf\u0131n\u0131\u201d yeniden olu\u015fturabiliyor. Bir \u00f6nceki resimdeki g\u00f6r\u00fcnt\u00fcn\u00fcn yakalanmas\u0131 17 dakika s\u00fcrm\u00fc\u015f. Bu h\u0131zlarda ger\u00e7ek zamanl\u0131 g\u00f6zetleme s\u00f6z konusu olamaz. Deneylerin \u00e7o\u011funda neden bir mankenin elinin kullan\u0131ld\u0131\u011f\u0131 da \u015fimdi anla\u015f\u0131l\u0131yor: Bir insan elini o kadar uzun s\u00fcre hareketsiz tutamaz.<\/p>\n

Ancak bu, y\u00f6ntemin geli\u015ftirilebilece\u011fi ihtimalini ortadan kald\u0131rm\u0131yor. En k\u00f6t\u00fc senaryoyu d\u00fc\u015f\u00fcnelim: e\u011fer her bir el g\u00f6r\u00fcnt\u00fcs\u00fc \u00fc\u00e7 dakika i\u00e7inde de\u011fil de \u00f6rne\u011fin yar\u0131m saniye i\u00e7inde elde edilebilirse; e\u011fer ekrandaki g\u00f6r\u00fcnt\u00fc garip siyah-beyaz fig\u00fcrler de\u011fil de kullan\u0131c\u0131n\u0131n ilgisini \u00e7ekecek bir video ya da bir dizi resim veya animasyon ise; ve e\u011fer kullan\u0131c\u0131 g\u00f6zetlemeye de\u011fer bir \u015fey yaparsa\u2026 \u0130\u015fte o zaman bir sald\u0131r\u0131 ger\u00e7ekle\u015ftirmek anlaml\u0131 olacakt\u0131r. Ama o zaman bile pek bir anlam ifade etmiyor. Ara\u015ft\u0131rmac\u0131lar\u0131n t\u00fcm \u00e7abalar\u0131, bir sald\u0131rgan kurban\u0131n cihaz\u0131na k\u00f6t\u00fc ama\u00e7l\u0131 yaz\u0131l\u0131m yerle\u015ftirmeyi ba\u015fard\u0131\u011f\u0131 takdirde, bir \u015fifre veya kredi kart\u0131 numaras\u0131 girmeleri i\u00e7in onlar\u0131 kand\u0131rman\u0131n daha kolay bir\u00e7ok yolu oldu\u011fu ger\u00e7e\u011fiyle baltalan\u0131yor. Belki de bu t\u00fcr makaleleri (\u00f6rnekler: bir<\/a>, iki<\/a>, \u00fc\u00e7<\/a>, d\u00f6rt<\/a>) haber yaparken ilk kez, b\u00f6yle bir sald\u0131r\u0131 i\u00e7in ger\u00e7ek hayattan bir senaryo hayal etmekte bile zorlan\u0131yoruz.<\/p>\n

Tek yapabilece\u011fimiz, sunulan y\u00f6ntemin g\u00fczelli\u011fine hayran kalmak. Bu ara\u015ft\u0131rma, etraf\u0131m\u0131z\u0131 saran, g\u00f6r\u00fcn\u00fc\u015fte tan\u0131d\u0131k, g\u00f6ze \u00e7arpmayan cihazlar\u0131n al\u0131\u015f\u0131lmad\u0131k, daha az bilinen daha ne i\u015flevler i\u00e7in kullan\u0131labilece\u011fini bize bir kez daha hat\u0131rlat\u0131yor. \u00d6te yandan, bu potansiyel gizlilik ihlalinden endi\u015fe duyanlar i\u00e7in \u00e7\u00f6z\u00fcm basittir. Bu t\u00fcr d\u00fc\u015f\u00fck kaliteli g\u00f6r\u00fcnt\u00fcler, \u0131\u015f\u0131k sens\u00f6r\u00fcn\u00fcn olduk\u00e7a seyrek \u00f6l\u00e7\u00fcm yapmas\u0131ndan kaynaklan\u0131r: Saniyede 10-20 kez. \u00c7\u0131kt\u0131 verileri de hassasiyetten yoksundur. Ancak, bu yaln\u0131zca sens\u00f6r\u00fc bir kameraya d\u00f6n\u00fc\u015ft\u00fcrmek istenmesi durumunda ge\u00e7erlidir. Ana g\u00f6rev olan ortam \u0131\u015f\u0131\u011f\u0131n\u0131 \u00f6l\u00e7mek i\u00e7in bu oran bile \u00e7ok y\u00fcksektir. Verileri daha da \u201ckabala\u015ft\u0131rabiliriz\u201d, \u00f6rne\u011fin saniyede 20 yerine be\u015f kez iletebiliriz. Ekran parlakl\u0131\u011f\u0131n\u0131 ortam \u0131\u015f\u0131\u011f\u0131 seviyesiyle e\u015fle\u015ftirmek i\u00e7in bu fazlas\u0131yla yeterlidir. Ancak sens\u00f6r arac\u0131l\u0131\u011f\u0131yla casusluk yapma olas\u0131l\u0131\u011f\u0131 zaten yok denecek kadar azken iyice imkans\u0131z hale gelecektir. Belki de b\u00f6ylesi daha iyi.<\/p>\n","protected":false},"excerpt":{"rendered":"

T\u00fcm modern ak\u0131ll\u0131 telefon ve tabletlerde bulunan standart bir \u00f6zelli\u011fin beklenmedik baz\u0131 nitelikleri \u00fczerine yeni bir \u00e7al\u0131\u015fma.<\/p>\n","protected":false},"author":665,"featured_media":12104,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1726,1194],"tags":[555,667,500],"class_list":{"0":"post-12101","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-enterprise","8":"category-business","9":"tag-akilli-telefonlar","10":"tag-arastirma","11":"tag-gizlilik"},"hreflang":[{"hreflang":"tr","url":"https:\/\/www.kaspersky.com.tr\/blog\/ambient-light-sensor-privacy\/12101\/"},{"hreflang":"en-in","url":"https:\/\/www.kaspersky.co.in\/blog\/ambient-light-sensor-privacy\/27035\/"},{"hreflang":"en-ae","url":"https:\/\/me-en.kaspersky.com\/blog\/ambient-light-sensor-privacy\/22347\/"},{"hreflang":"ar","url":"https:\/\/me.kaspersky.com\/blog\/ambient-light-sensor-privacy\/11466\/"},{"hreflang":"en-us","url":"https:\/\/usa.kaspersky.com\/blog\/ambient-light-sensor-privacy\/29704\/"},{"hreflang":"en-gb","url":"https:\/\/www.kaspersky.co.uk\/blog\/ambient-light-sensor-privacy\/27202\/"},{"hreflang":"es-mx","url":"https:\/\/latam.kaspersky.com\/blog\/ambient-light-sensor-privacy\/27073\/"},{"hreflang":"es","url":"https:\/\/www.kaspersky.es\/blog\/ambient-light-sensor-privacy\/29750\/"},{"hreflang":"it","url":"https:\/\/www.kaspersky.it\/blog\/ambient-light-sensor-privacy\/28576\/"},{"hreflang":"ru","url":"https:\/\/www.kaspersky.ru\/blog\/ambient-light-sensor-privacy\/36932\/"},{"hreflang":"x-default","url":"https:\/\/www.kaspersky.com\/blog\/ambient-light-sensor-privacy\/50473\/"},{"hreflang":"fr","url":"https:\/\/www.kaspersky.fr\/blog\/ambient-light-sensor-privacy\/21582\/"},{"hreflang":"pt-br","url":"https:\/\/www.kaspersky.com.br\/blog\/ambient-light-sensor-privacy\/22294\/"},{"hreflang":"de","url":"https:\/\/www.kaspersky.de\/blog\/ambient-light-sensor-privacy\/30980\/"},{"hreflang":"ru-kz","url":"https:\/\/blog.kaspersky.kz\/ambient-light-sensor-privacy\/27422\/"},{"hreflang":"en-au","url":"https:\/\/www.kaspersky.com.au\/blog\/ambient-light-sensor-privacy\/33219\/"},{"hreflang":"en-za","url":"https:\/\/www.kaspersky.co.za\/blog\/ambient-light-sensor-privacy\/32843\/"}],"acf":[],"banners":"","maintag":{"url":"https:\/\/www.kaspersky.com.tr\/blog\/tag\/akilli-telefonlar\/","name":"ak\u0131ll\u0131 telefonlar"},"_links":{"self":[{"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/posts\/12101","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/users\/665"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/comments?post=12101"}],"version-history":[{"count":4,"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/posts\/12101\/revisions"}],"predecessor-version":[{"id":12119,"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/posts\/12101\/revisions\/12119"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/media\/12104"}],"wp:attachment":[{"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/media?parent=12101"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/categories?post=12101"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kaspersky.com.tr\/blog\/wp-json\/wp\/v2\/tags?post=12101"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}