{"id":941,"date":"2026-02-03T20:01:35","date_gmt":"2026-02-03T17:01:35","guid":{"rendered":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/"},"modified":"2026-02-03T20:01:58","modified_gmt":"2026-02-03T17:01:58","slug":"llm-data-leakage-ai-risk","status":"publish","type":"post","link":"https:\/\/neku.ai\/en\/llm-data-leakage-ai-risk\/","title":{"rendered":"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri"},"content":{"rendered":"

LLM Kullanan Sistemlerde Data Leakage Riski<\/strong><\/h1>\n
\n

Giri\u015f<\/strong><\/h3>\n

LLM (Large Language Model) tabanl\u0131 sistemlerde data leakage ai<\/strong>, yani veri s\u0131z\u0131nt\u0131s\u0131 riski, son d\u00f6nemde kurumsal yapay zeka uygulamalar\u0131nda en kritik g\u00fcvenlik ba\u015fl\u0131klar\u0131ndan biri haline geldi. Bu risk, gizli veya hassas bilgilerin yanl\u0131\u015fl\u0131kla model yan\u0131tlar\u0131na s\u0131zmas\u0131, e\u011fitim verilerine aktar\u0131lmas\u0131 ya da \u00fc\u00e7\u00fcnc\u00fc taraf API\u2019ler \u00fczerinden d\u0131\u015far\u0131 ta\u015f\u0131nmas\u0131yla ortaya \u00e7\u0131kar. G\u00fcvenlik odakl\u0131 kurumlar i\u00e7in bu durum yaln\u0131zca teknik de\u011fil, ayn\u0131 zamanda yasal ve kurumsal bir problem olarak de\u011ferlendirilir. <\/p>\n

\n

LLM Kullanan Sistemlerde Data Leakage Riski tan\u0131m\u0131<\/strong><\/h3>\n

LLM kullanan sistemlerde data leakage ai<\/strong>, modelin eri\u015fti\u011fi veya i\u015fledi\u011fi verilerin yetkisiz bi\u00e7imde d\u0131\u015fa s\u0131zmas\u0131d\u0131r. Bu s\u0131z\u0131nt\u0131 genellikle kullan\u0131c\u0131 girdileri, e\u011fitim veri havuzlar\u0131 veya model \u00e7\u0131kt\u0131lar\u0131 arac\u0131l\u0131\u011f\u0131yla olu\u015fur. \u00d6zellikle kurumsal seviyede, bu t\u00fcr bir s\u0131z\u0131nt\u0131 hem i\u00e7 a\u011f g\u00fcvenli\u011fini hem de m\u00fc\u015fteri verilerini do\u011frudan etkileyebilir. <\/p>\n

\n

data leakage ai nas\u0131l \u00e7al\u0131\u015f\u0131r<\/strong><\/h3>\n

data leakage ai<\/strong> kavram\u0131, LLM\u2019in e\u011fitim, ince ayar veya ger\u00e7ek zamanl\u0131 kullan\u0131m a\u015famalar\u0131nda ger\u00e7ekle\u015fen veri ak\u0131\u015f\u0131na ba\u011fl\u0131 \u015fekilde i\u015fler. Modelin mimarisi, kullan\u0131lan API\u2019ler, prompt ge\u00e7mi\u015fi ve \u00f6nbellek mekanizmalar\u0131 bu riski belirleyen ana bile\u015fenlerdir. <\/p>\n

Temel parametreler ve ayarlar<\/strong><\/h4>\n
    \n
  • Veri eri\u015fim politikalar\u0131:<\/strong> LLM, yaln\u0131zca yetkili veri kaynaklar\u0131n\u0131 kullanmal\u0131d\u0131r. <\/li>\n
  • Model logging d\u00fczeyi:<\/strong> Kullan\u0131c\u0131 girdilerinin kaydedildi\u011fi log sistemleri anonimle\u015ftirilmelidir. <\/li>\n
  • Token s\u00fcresi ve g\u00fcvenli oturum y\u00f6netimi:<\/strong> Oturum a\u00e7ma anahtarlar\u0131n\u0131n ya\u015fam s\u00fcresi k\u0131sa olmal\u0131d\u0131r. <\/li>\n
  • LLM security protokolleri:<\/strong> Model eri\u015fimini s\u0131n\u0131rlamak i\u00e7in IAM (Identity Access Management) sistemleriyle entegrasyon kritiktir. <\/li>\n<\/ul>\n

    S\u0131k yap\u0131lan hatalar ve ka\u00e7\u0131nma y\u00f6ntemleri<\/strong><\/h4>\n
      \n
    • A\u015f\u0131r\u0131 veri payla\u015f\u0131m\u0131:<\/strong> Gereksiz metin veya sistem \u00e7\u0131kt\u0131lar\u0131n\u0131n modele g\u00f6nderilmemesi gerekir. <\/li>\n
    • Model \u00e7\u0131kt\u0131lar\u0131n\u0131n do\u011frulanmamas\u0131:<\/strong> Cevaplar, veri s\u0131z\u0131nt\u0131s\u0131 kontrol algoritmalar\u0131yla taranmal\u0131d\u0131r. <\/li>\n
    • Prompt engineering hatalar\u0131:<\/strong> Gizli bilgileri istem d\u0131\u015f\u0131 ortaya \u00e7\u0131karabilecek komutlardan ka\u00e7\u0131n\u0131lmal\u0131d\u0131r. <\/li>\n<\/ul>\n

      Ger\u00e7ek sistemlerde uygulama \u00f6rnekleri<\/strong><\/h4>\n

      Bir kurum i\u00e7i chatbot uygulamas\u0131nda kullan\u0131c\u0131, m\u00fc\u015fteri verisine ili\u015fkin sorgular yapt\u0131\u011f\u0131nda model bu bilgileri do\u011frudan yan\u0131ta dahil etmemelidir. Bunun yerine LLM, anonimle\u015ftirilmi\u015f \u00f6zetler veya kimliksiz veri k\u00fcmeleri \u00fczerinden yan\u0131t \u00fcretmelidir. <\/p>\n

      \n

      Teknik a\u00e7\u0131klama (derin seviye)<\/strong><\/h3>\n

      LLM, \u00e7ok b\u00fcy\u00fck metin veri setleriyle e\u011fitilir ve bu veri setleri modelin olas\u0131l\u0131k da\u011f\u0131l\u0131m\u0131n\u0131 belirler. E\u011fer e\u011fitim verileri i\u00e7inde kimlik, finansal kay\u0131t veya tescilli bilgi yer al\u0131yorsa, bu bilgiler model yan\u0131tlar\u0131nda istatistiksel olarak yeniden \u00fcretilebilir. data leakage ai<\/strong> bu durumda i\u00e7sel hale gelir; yani s\u0131z\u0131nt\u0131 d\u0131\u015f sistemden de\u011fil, modelin haf\u0131zas\u0131ndan kaynaklan\u0131r. <\/p>\n

      llm security<\/strong> kapsam\u0131nda \u00e7\u00f6z\u00fcm, katmanl\u0131 bir yakla\u015f\u0131m gerektirir: E\u011fitim verilerinde anonimle\u015ftirme, kullan\u0131m a\u015famas\u0131nda eri\u015fim kontrol\u00fc, \u00e7\u0131kt\u0131 sonras\u0131 veri do\u011frulama. Ayr\u0131ca token tabanl\u0131 g\u00fcvenlik, model IO (Input\/Output) izleme sistemleriyle desteklenmelidir. <\/p>\n

      \n

      \u0130\u015fletmeler i\u00e7in neden kritiktir<\/strong><\/h3>\n
        \n
      • Performans:<\/strong> Veri s\u0131z\u0131nt\u0131s\u0131 riskini azaltmak i\u00e7in yap\u0131lan g\u00fcvenlik katmanlar\u0131 model yan\u0131t s\u00fcresini etkileyebilir. <\/li>\n
      • G\u00fcvenilirlik:<\/strong> Modellerin tutarl\u0131 ve g\u00fcvenli veri \u00fcretmesi marka itibar\u0131 i\u00e7in zorunludur. <\/li>\n
      • Maliyet:<\/strong> Yanl\u0131\u015f g\u00fcvenlik yap\u0131land\u0131rmalar\u0131 y\u00fcksek uyumluluk maliyetlerine yol a\u00e7ar. <\/li>\n
      • \u00d6l\u00e7ekleme:<\/strong> Artan kullan\u0131c\u0131 say\u0131s\u0131yla birlikte veri koruma s\u00fcre\u00e7leri de \u00f6l\u00e7eklenebilir olmal\u0131d\u0131r. <\/li>\n
      • Otomasyon:<\/strong> S\u00fcrekli tehdit analizi ve otomatik do\u011frulama mekanizmalar\u0131 gereklidir. <\/li>\n
      • Karar alma:<\/strong> LLM\u2019den gelen i\u00e7g\u00f6r\u00fclerin g\u00fcvenilirli\u011fi do\u011frudan veri b\u00fct\u00fcnl\u00fc\u011f\u00fcne ba\u011fl\u0131d\u0131r. <\/li>\n
      • Operasyonel verimlilik:<\/strong> G\u00fcvenli veri ak\u0131\u015f\u0131 sistem kararl\u0131l\u0131\u011f\u0131n\u0131 art\u0131r\u0131r. <\/li>\n<\/ul>\n
        \n

        Bu kavram NeKu.AI i\u00e7inde nas\u0131l uygulan\u0131r<\/strong><\/h3>\n

        NeKu.AI, kurumsal AI platform mimarisinde veri izolasyonu ve g\u00fcvenli i\u015flem katmanlar\u0131n\u0131 \u00f6nceliklendirir. Model e\u011fitimi ve \u00e7\u0131kar\u0131m (inference) s\u00fcre\u00e7leri, ayr\u0131 a\u011f b\u00f6lgelerinde ger\u00e7ekle\u015ftirilerek hassas bilgilerin yan\u0131t y\u00fczeyine kar\u0131\u015fmas\u0131 engellenir. <\/p>\n

        Platform, llm security<\/strong> prensiplerini uygulamak i\u00e7in \u015fifreli veri ge\u00e7itleri, API eri\u015fim kontrol\u00fc ve denetlenebilir i\u015flem loglar\u0131 kullan\u0131r. Bu yakla\u015f\u0131m, veri koruma \u00f6nlemlerini LLM kullan\u0131m\u0131n\u0131n do\u011fal bir par\u00e7as\u0131 haline getirir. <\/p>\n

        \n

        CTO, CIO, \u00fcr\u00fcn y\u00f6neticileri i\u00e7in ger\u00e7ek bir senaryo<\/strong><\/h3>\n
          \n
        1. Sorun:<\/strong> Kurum i\u00e7i bilgi y\u00f6netim sistemi LLM tabanl\u0131 bir destek botuna ba\u011flan\u0131yor. Kullan\u0131c\u0131lar dahili veritabanlar\u0131ndan al\u0131nan i\u00e7erikleri sorguluyor. <\/li>\n
        2. Ba\u011flam:<\/strong> Baz\u0131 kullan\u0131c\u0131 sorgular\u0131 m\u00fc\u015fteri s\u00f6zle\u015fmelerindeki kritik metinleri modelin yan\u0131t\u0131na dahil ediyor. <\/li>\n
        3. Kavram\u0131n uygulanmas\u0131:<\/strong> Eri\u015fim kontrol mekanizmalar\u0131 devreye al\u0131narak veri s\u0131n\u0131fland\u0131rmas\u0131 yap\u0131l\u0131yor. Model yaln\u0131zca anonimle\u015ftirilmi\u015f \u00f6zetlerle \u00e7al\u0131\u015f\u0131yor. <\/li>\n
        4. Sonu\u00e7:<\/strong> data leakage ai<\/strong> riski belirgin bi\u00e7imde azal\u0131yor, model yaln\u0131zca g\u00fcvenli i\u00e7erik \u00fcretiyor. <\/li>\n
        5. \u0130\u015f etkisi:<\/strong> G\u00fcvenlik denetimlerinden ge\u00e7mek kolayla\u015f\u0131yor, sistemin g\u00fcven seviyesi art\u0131yor. <\/li>\n<\/ol>\n
          \n

          S\u0131k yap\u0131lan hatalar ve en iyi uygulamalar<\/strong><\/h3>\n

          Yayg\u0131n hatalar:<\/strong> <\/p>\n

            \n
          • Log sisteminde kullan\u0131c\u0131 verilerinin d\u00fcz metin olarak tutulmas\u0131 <\/li>\n
          • API anahtarlar\u0131n\u0131n payla\u015f\u0131lmas\u0131 <\/li>\n
          • E\u011fitim veri setlerinin anonimle\u015ftirilmemesi <\/li>\n
          • Model yan\u0131tlar\u0131n\u0131n \u00fcretim \u00f6ncesi denetimden ge\u00e7memesi <\/li>\n<\/ul>\n

            En iyi uygulamalar:<\/strong> <\/p>\n

              \n
            • Veri s\u0131n\u0131fland\u0131rmas\u0131 ve maskeleme s\u00fcre\u00e7lerini otomatikle\u015ftirin <\/li>\n
            • LLM eri\u015fim katmanlar\u0131nda IAM entegrasyonuna \u00f6ncelik verin <\/li>\n
            • Prompt ge\u00e7mi\u015fini d\u00fczenli olarak denetleyin <\/li>\n
            • Her model s\u00fcr\u00fcm\u00fc i\u00e7in g\u00fcvenlik testleri uygulay\u0131n <\/li>\n<\/ul>\n
              \n

              Sonu\u00e7<\/strong><\/h3>\n

              LLM tabanl\u0131 sistemlerde data leakage ai<\/strong> riski, yaln\u0131zca teknik de\u011fil stratejik bir g\u00fcvenlik konusudur. Kurumun veri yap\u0131s\u0131, eri\u015fim politikalar\u0131 ve model mimarisi bu riski y\u00f6netmenin temelidir. Etkin llm security<\/strong> uygulamalar\u0131, yaln\u0131zca veriyi de\u011fil, ayn\u0131 zamanda kurumun b\u00fct\u00fcn yapay zeka ekosistemini korur. <\/p>\n

              NeKu.AI gibi kurumsal AI platformlar\u0131nda bu yakla\u015f\u0131m, g\u00fcvenli otomasyonun ve \u00f6l\u00e7eklenebilir yapay zeka uygulamalar\u0131n\u0131n s\u00fcrd\u00fcr\u00fclebilir temelini olu\u015fturur.<\/p>","protected":false},"excerpt":{"rendered":"

              LLM Kullanan Sistemlerde Data Leakage Riski Giri\u015f LLM (Large Language Model) tabanl\u0131 sistemlerde data leakage ai, yani veri s\u0131z\u0131nt\u0131s\u0131 riski, son d\u00f6nemde kurumsal yapay zeka uygulamalar\u0131nda [\u2026]<\/span><\/p>\n","protected":false},"author":2,"featured_media":942,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_sitemap_exclude":false,"_sitemap_priority":"","_sitemap_frequency":"","footnotes":""},"categories":[],"tags":[],"class_list":["post-941","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry"],"yoast_head":"\nLLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri - NeKu.AI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/neku.ai\/en\/llm-data-leakage-ai-risk\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri - NeKu.AI\" \/>\n<meta property=\"og:description\" content=\"LLM Kullanan Sistemlerde Data Leakage Riski Giri\u015f LLM (Large Language Model) tabanl\u0131 sistemlerde data leakage ai, yani veri s\u0131z\u0131nt\u0131s\u0131 riski, son d\u00f6nemde kurumsal yapay zeka uygulamalar\u0131nda [\u2026]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/neku.ai\/en\/llm-data-leakage-ai-risk\/\" \/>\n<meta property=\"og:site_name\" content=\"NeKu.AI\" \/>\n<meta property=\"article:published_time\" content=\"2026-02-03T17:01:35+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-02-03T17:01:58+00:00\" \/>\n<meta name=\"author\" content=\"Serkan \u00d6zcan\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Serkan \u00d6zcan\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/\"},\"author\":{\"name\":\"Serkan \u00d6zcan\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/person\\\/cf640cfda3e16635fb740662d943e96b\"},\"headline\":\"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri\",\"datePublished\":\"2026-02-03T17:01:35+00:00\",\"dateModified\":\"2026-02-03T17:01:58+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/\"},\"wordCount\":1037,\"publisher\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2026\\\/02\\\/cover-image-941.jpg\",\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/\",\"url\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/\",\"name\":\"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri - NeKu.AI\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2026\\\/02\\\/cover-image-941.jpg\",\"datePublished\":\"2026-02-03T17:01:35+00:00\",\"dateModified\":\"2026-02-03T17:01:58+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/#primaryimage\",\"url\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2026\\\/02\\\/cover-image-941.jpg\",\"contentUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2026\\\/02\\\/cover-image-941.jpg\",\"width\":1024,\"height\":1024},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/neku.ai\\\/llm-data-leakage-ai-risk\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Anasayfa\",\"item\":\"https:\\\/\\\/neku.ai\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#website\",\"url\":\"https:\\\/\\\/neku.ai\\\/\",\"name\":\"NeKuAI\",\"description\":\"\u0130\u015fletmenizi daha "Ak\u0131ll\u0131" yap\u0131n\",\"publisher\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/neku.ai\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#organization\",\"name\":\"NeKuAI\",\"url\":\"https:\\\/\\\/neku.ai\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/02\\\/apple-icon-180x180-1.png\",\"contentUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/02\\\/apple-icon-180x180-1.png\",\"width\":180,\"height\":180,\"caption\":\"NeKuAI\"},\"image\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/logo\\\/image\\\/\"}},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/person\\\/cf640cfda3e16635fb740662d943e96b\",\"name\":\"Serkan \u00d6zcan\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/plugins\\\/swiss-toolkit-for-wp\\\/\\\/admin\\\/img\\\/default-avatar.png\",\"url\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/plugins\\\/swiss-toolkit-for-wp\\\/\\\/admin\\\/img\\\/default-avatar.png\",\"contentUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/plugins\\\/swiss-toolkit-for-wp\\\/\\\/admin\\\/img\\\/default-avatar.png\",\"caption\":\"Serkan \u00d6zcan\"},\"url\":\"https:\\\/\\\/neku.ai\\\/en\\\/author\\\/serkanozcan\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri - NeKu.AI","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/neku.ai\/en\/llm-data-leakage-ai-risk\/","og_locale":"en_US","og_type":"article","og_title":"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri - NeKu.AI","og_description":"LLM Kullanan Sistemlerde Data Leakage Riski Giri\u015f LLM (Large Language Model) tabanl\u0131 sistemlerde data leakage ai, yani veri s\u0131z\u0131nt\u0131s\u0131 riski, son d\u00f6nemde kurumsal yapay zeka uygulamalar\u0131nda [\u2026]","og_url":"https:\/\/neku.ai\/en\/llm-data-leakage-ai-risk\/","og_site_name":"NeKu.AI","article_published_time":"2026-02-03T17:01:35+00:00","article_modified_time":"2026-02-03T17:01:58+00:00","author":"Serkan \u00d6zcan","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Serkan \u00d6zcan","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/#article","isPartOf":{"@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/"},"author":{"name":"Serkan \u00d6zcan","@id":"https:\/\/neku.ai\/#\/schema\/person\/cf640cfda3e16635fb740662d943e96b"},"headline":"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri","datePublished":"2026-02-03T17:01:35+00:00","dateModified":"2026-02-03T17:01:58+00:00","mainEntityOfPage":{"@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/"},"wordCount":1037,"publisher":{"@id":"https:\/\/neku.ai\/#organization"},"image":{"@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/#primaryimage"},"thumbnailUrl":"https:\/\/neku.ai\/wp-content\/uploads\/2026\/02\/cover-image-941.jpg","inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/","url":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/","name":"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri - NeKu.AI","isPartOf":{"@id":"https:\/\/neku.ai\/#website"},"primaryImageOfPage":{"@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/#primaryimage"},"image":{"@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/#primaryimage"},"thumbnailUrl":"https:\/\/neku.ai\/wp-content\/uploads\/2026\/02\/cover-image-941.jpg","datePublished":"2026-02-03T17:01:35+00:00","dateModified":"2026-02-03T17:01:58+00:00","breadcrumb":{"@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/neku.ai\/llm-data-leakage-ai-risk\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/#primaryimage","url":"https:\/\/neku.ai\/wp-content\/uploads\/2026\/02\/cover-image-941.jpg","contentUrl":"https:\/\/neku.ai\/wp-content\/uploads\/2026\/02\/cover-image-941.jpg","width":1024,"height":1024},{"@type":"BreadcrumbList","@id":"https:\/\/neku.ai\/llm-data-leakage-ai-risk\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Anasayfa","item":"https:\/\/neku.ai\/"},{"@type":"ListItem","position":2,"name":"LLM Sistemlerinde Data Leakage Riskini Azaltma Y\u00f6ntemleri"}]},{"@type":"WebSite","@id":"https:\/\/neku.ai\/#website","url":"https:\/\/neku.ai\/","name":"NeKuAI","description":"\u0130\u015fletmenizi daha "Ak\u0131ll\u0131" yap\u0131n","publisher":{"@id":"https:\/\/neku.ai\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/neku.ai\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/neku.ai\/#organization","name":"NeKuAI","url":"https:\/\/neku.ai\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/neku.ai\/#\/schema\/logo\/image\/","url":"https:\/\/neku.ai\/wp-content\/uploads\/2025\/02\/apple-icon-180x180-1.png","contentUrl":"https:\/\/neku.ai\/wp-content\/uploads\/2025\/02\/apple-icon-180x180-1.png","width":180,"height":180,"caption":"NeKuAI"},"image":{"@id":"https:\/\/neku.ai\/#\/schema\/logo\/image\/"}},{"@type":"Person","@id":"https:\/\/neku.ai\/#\/schema\/person\/cf640cfda3e16635fb740662d943e96b","name":"Serkan \u00d6zcan","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/neku.ai\/wp-content\/plugins\/swiss-toolkit-for-wp\/\/admin\/img\/default-avatar.png","url":"https:\/\/neku.ai\/wp-content\/plugins\/swiss-toolkit-for-wp\/\/admin\/img\/default-avatar.png","contentUrl":"https:\/\/neku.ai\/wp-content\/plugins\/swiss-toolkit-for-wp\/\/admin\/img\/default-avatar.png","caption":"Serkan \u00d6zcan"},"url":"https:\/\/neku.ai\/en\/author\/serkanozcan\/"}]}},"_links":{"self":[{"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/posts\/941","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/comments?post=941"}],"version-history":[{"count":0,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/posts\/941\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/media\/942"}],"wp:attachment":[{"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/media?parent=941"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/categories?post=941"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/tags?post=941"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}