{"id":998428,"date":"2026-07-23T11:08:08","date_gmt":"2026-07-23T08:08:08","guid":{"rendered":"https:\/\/www.morten.com.tr\/?p=998428"},"modified":"2026-07-23T11:08:35","modified_gmt":"2026-07-23T08:08:35","slug":"geleneksel-siemin-otesi-splunk-ile-ai-destekli-siber-savunma-ve-tehdit-avciligi","status":"publish","type":"post","link":"https:\/\/www.morten.com.tr\/en\/geleneksel-siemin-otesi-splunk-ile-ai-destekli-siber-savunma-ve-tehdit-avciligi\/","title":{"rendered":"Geleneksel SIEM’in \u00d6tesi: Splunk ile AI Destekli Siber Savunma ve Tehdit Avc\u0131l\u0131\u011f\u0131"},"content":{"rendered":"
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Yazar:\u00a0 Huzeyfe Himmeto\u011flu | Ankara – Teknik Operasyonlar Birim M\u00fcd\u00fcr\u00fc
<\/strong><\/p>

Siber tehdit akt\u00f6rleri her ge\u00e7en g\u00fcn daha sofistike, h\u0131zl\u0131 ve yapay zeka destekli sald\u0131r\u0131 y\u00f6ntemleri geli\u015ftiriyor. G\u00fcn\u00fcm\u00fczde bir kurumun dijital varl\u0131klar\u0131n\u0131 korumak; her saniye binlerce cihazdan, bulut altyap\u0131s\u0131ndan ve u\u00e7 noktadan (endpoint) akan milyonlarca log sat\u0131r\u0131n\u0131 analiz etmeyi gerektiriyor. Geleneksel, yaln\u0131zca statik kurallara dayal\u0131 SIEM (G\u00fcvenlik Bilgi ve Olay Y\u00f6netimi) sistemleri, bu devasa veri tsunami kar\u015f\u0131s\u0131nda yetersiz kal\u0131yor; y\u00fcksek oranda yanl\u0131\u015f pozitif (false positive) alarm \u00fcreterek siber g\u00fcvenlik analistlerinde alarm yorgunlu\u011funa (alert fatigue)<\/strong> yol a\u00e7\u0131yor.<\/p>

Siber g\u00fcvenlik operasyonlar\u0131nda (SecOps) yeni bir \u00e7a\u011f a\u00e7an Splunk Enterprise Security (ES)<\/strong>, arkas\u0131ndaki yapay zeka (AI) ve makine \u00f6\u011frenimi (ML) g\u00fcc\u00fcyle siber savunmay\u0131 reaktif bir \u00e7izgiden proaktif ve tahmine dayal\u0131 bir boyuta ta\u015f\u0131yor.<\/p>

Mimari Temel: Splunk Machine Learning Toolkit (MLTK) ve SIEM Entegrasyonu<\/strong><\/h5>

Splunk’\u0131n yapay zeka destekli SIEM mimarisinin kalbinde, platformun ham veri i\u015fleme g\u00fcc\u00fcyle b\u00fct\u00fcnle\u015fik \u00e7al\u0131\u015fan Splunk Machine Learning Toolkit (MLTK)<\/strong> yer al\u0131r. Geleneksel SIEM’ler sadece “E\u011fer A olay\u0131 ve B olay\u0131 ger\u00e7ekle\u015firse alarm \u00fcret” mant\u0131\u011f\u0131yla \u00e7al\u0131\u015f\u0131rken, AI destekli Splunk \u015fu matematiksel ve istatistiksel modelleri kullan\u0131r:<\/p>

  • Davran\u0131\u015fsal Temel \u00c7izgi (Behavioral Baselining):<\/strong> Yapay zeka, a\u011fdaki kullan\u0131c\u0131lar\u0131n, sunucular\u0131n ve servislerin g\u00fcnl\u00fck rutin davran\u0131\u015f kal\u0131plar\u0131n\u0131 (baseline) s\u00fcrekli izleyerek \u00f6\u011frenir. Bir kullan\u0131c\u0131n\u0131n normalde eri\u015fmedi\u011fi kritik bir veritaban\u0131na, al\u0131\u015f\u0131lmad\u0131k bir saatte ve y\u00fcksek hacimli veri \u00e7ekecek \u015fekilde eri\u015fmesi, statik kurallar\u0131 ihlal etmese bile AI taraf\u0131ndan bir anomali olarak etiketlenir.<\/li>
  • Geli\u015fmi\u015f K\u00fcmeleme ve S\u0131n\u0131fland\u0131rma (Clustering & Classification):<\/strong> Milyonlarca log sat\u0131r\u0131 i\u00e7indeki benzer hareketler (\u00f6rne\u011fin arka arkaya denenen ba\u015far\u0131s\u0131z oturum a\u00e7ma istekleri veya mikro a\u011f taramalar\u0131) yapay zeka taraf\u0131ndan otomatik olarak grupland\u0131r\u0131l\u0131r. Bu sayede da\u011f\u0131n\u0131k haldeki y\u00fczlerce k\u00fc\u00e7\u00fck sinyal, tek bir organize sald\u0131r\u0131 zinciri olarak anlamland\u0131r\u0131l\u0131r.<\/li><\/ul>
    AI Destekli Splunk SIEM\u2019in G\u00fcvenlik Operasyonlar\u0131na 3 Kritik Katk\u0131s\u0131<\/strong><\/h5>

    A. Bilinmeyen Tehditlerin (Zero-Day) Yakalanmas\u0131<\/strong><\/p>

    Geleneksel SIEM’ler, sald\u0131r\u0131lar\u0131 tespit etmek i\u00e7in bilinen tehdit imzalar\u0131na (signatures) veya \u00f6nceden yaz\u0131lm\u0131\u015f korelasyon kurallar\u0131na ihtiya\u00e7 duyar. Ancak s\u0131f\u0131r\u0131nc\u0131 g\u00fcn (Zero-Day) sald\u0131r\u0131lar\u0131nda ortada hen\u00fcz bir imza yoktur. Splunk\u2019\u0131n AI motorlar\u0131, MITRE ATT&CK<\/strong> matrisini referans alarak verilerdeki gizli sapmalar\u0131, yanal ilerleme (lateral movement) ad\u0131mlar\u0131n\u0131 ve veri s\u0131zd\u0131rma (exfiltration) anomalilerini hen\u00fcz sald\u0131r\u0131 olgunla\u015fmadan tespit eder.<\/p>

    B. Alarm Yorgunlu\u011funun \u00d6nlenmesi ve Ak\u0131ll\u0131 \u00d6nceliklendirme<\/strong><\/p>

    Bir SOC (G\u00fcvenlik Operasyon Merkezi) analistinin g\u00fcnde y\u00fczlerce sahte alarm\u0131 incelemesi verimlili\u011fi yok eder. Splunk, siber g\u00fcvenlik alarmlar\u0131n\u0131 yapay zeka s\u00fczgecinden ge\u00e7irerek g\u00fcr\u00fclt\u00fcy\u00fc temizler. Alarmlar\u0131 risk skorlamas\u0131na tabi tutar; kurumun kritik varl\u0131klar\u0131na (crown jewels) y\u00f6nelen ve anomalilik derecesi en y\u00fcksek olan vakalar\u0131 en \u00fcst s\u0131raya ta\u015f\u0131yarak analistlerin sadece “ger\u00e7ek” tehditlere odaklanmas\u0131n\u0131 sa\u011flar.<\/p>

    C. Splunk SOAR ile Otonom M\u00fcdahale (Playbook Otomasyonu)<\/strong><\/p>

    Yapay zeka sadece tespitte de\u011fil, m\u00fcdahalede de rol oynar. Splunk SIEM, AI algoritmalar\u0131yla do\u011frulu\u011fundan emin oldu\u011fu bir tehdidi (\u00f6rne\u011fin kesinle\u015fmi\u015f bir ransomware aktivitesi veya zararl\u0131 bir IP ile konu\u015fan bir u\u00e7 nokta) Splunk SOAR (Security Orchestration, Automation, and Response)<\/strong> katman\u0131na iletir. \u0130nsan m\u00fcdahalesine gerek kalmadan, milisaniyeler i\u00e7inde ilgili cihaz a\u011fdan izole edilir, kullan\u0131c\u0131 hesab\u0131 ask\u0131ya al\u0131n\u0131r veya firewall \u00fczerinde IP engellenir.<\/p>

    Biz Ne Sunuyoruz? \u0130leri D\u00fczey Splunk SIEM ve AI M\u00fchendisli\u011fi<\/strong><\/p>

    Veri analiti\u011finin zirvesi olan Splunk ile yapay zekan\u0131n g\u00fcc\u00fcn\u00fc birle\u015ftirmek, hem derin siber g\u00fcvenlik vizyonu hem de ileri d\u00fczey veri m\u00fchendisli\u011fi yetkinli\u011fi gerektirir. \u015eirketimiz, kurumunuzun siber dayan\u0131kl\u0131l\u0131\u011f\u0131n\u0131 en \u00fcst seviyeye \u00e7\u0131karmak i\u00e7in \u015fu katma de\u011ferli hizmetleri sunmaktad\u0131r:<\/p>

    • AI Tabanl\u0131 SIEM Mimari Tasar\u0131m\u0131:<\/strong> Log kaynaklar\u0131n\u0131z\u0131n Splunk Enterprise Security platformuna en optimum filtreleme teknikleriyle entegre edilmesini sa\u011fl\u0131yor, donan\u0131m y\u00fck\u00fcn\u00fc hafifletirken g\u00f6r\u00fcn\u00fcrl\u00fc\u011f\u00fc maksimuma \u00e7\u0131kar\u0131yoruz.<\/li>
    • Uygulamal\u0131 ve G\u00fcvenli PoC S\u00fcre\u00e7leri:<\/strong> Yat\u0131r\u0131m karar\u0131n\u0131z \u00f6ncesinde, kendi canl\u0131 a\u011f ortam\u0131n\u0131zda Splunk SIEM\u2019in ve yapay zeka modellerinin \u00fcretti\u011fi katma de\u011feri, yanl\u0131\u015f pozitifleri nas\u0131l temizledi\u011fini Proof of Concept (PoC)<\/strong> s\u00fcre\u00e7lerimizle somut olarak raporluyoruz.<\/li>
    • Kuruma \u00d6zel Korelasyon ve ML Modelleri:<\/strong> Sekt\u00f6r\u00fcn\u00fcze, reg\u00fclasyonlar\u0131n\u0131za ve siber tehdit matrisinize \u00f6zel SPL sorgular\u0131, makine \u00f6\u011frenimi modelleri ve anl\u0131k izleme panolar\u0131 (dashboard) geli\u015ftiriyoruz.<\/li><\/ul>

      Sonu\u00e7: Siber Savunmada Yapay Zeka H\u0131z\u0131<\/strong><\/p>

      Geleneksel y\u00f6ntemlerle modern siber tehditlerin h\u0131z\u0131na yeti\u015fmek art\u0131k imkans\u0131z. Splunk\u2019\u0131n b\u00fcy\u00fck veri i\u015fleme yetene\u011fi, yapay zekan\u0131n analitik zekas\u0131yla birle\u015fti\u011finde SecOps ekiplerinize adeta bir s\u00fcper g\u00fc\u00e7 kazand\u0131r\u0131r. Tehditleri saniyeler i\u00e7inde yakalamak, alarm yorgunlu\u011funu tarihe g\u00f6mmek ve AI destekli Splunk SIEM d\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fc ba\u015flatmak i\u00e7in uzman m\u00fchendislik kadromuzla ileti\u015fime ge\u00e7ebilirsiniz.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

      Yazar: \u00a0Huzeyfe Himmeto\u011flu | Ankara – Teknik Operasyonlar Birim M\u00fcd\u00fcr\u00fc<\/p>\n

      Siber tehdit akt\u00f6rleri her ge\u00e7en g\u00fcn daha sofistike, h\u0131zl\u0131 ve yapay zeka destekli sald\u0131r\u0131 y\u00f6ntemleri geli\u015ftiriyor. G\u00fcn\u00fcm\u00fczde bir kurumun dijital varl\u0131klar\u0131n\u0131 korumak; her saniye binlerce cihazdan, bulut altyap\u0131s\u0131ndan ve u\u00e7 noktadan (endpoint) akan milyonlarca log sat\u0131r\u0131n\u0131 analiz etmeyi gerektiriyor. Geleneksel, yaln\u0131zca statik kurallara dayal\u0131 SIEM (G\u00fcvenlik Bilgi ve Olay Y\u00f6netimi) sistemleri, bu devasa veri tsunami kar\u015f\u0131s\u0131nda yetersiz kal\u0131yor; y\u00fcksek oranda yanl\u0131\u015f pozitif (false positive) alarm \u00fcreterek siber g\u00fcvenlik analistlerinde alarm yorgunlu\u011funa (alert fatigue) yol a\u00e7\u0131yor.<\/p>","protected":false},"author":11,"featured_media":998430,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[117,115,205],"tags":[224,223,222,221],"class_list":["post-998428","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-networking","category-security-blog","category-yapay-zeka","tag-ai-destekli-siem","tag-enterprise-security","tag-siem","tag-splunk"],"yoast_head":"\nGeleneksel SIEM'in \u00d6tesi: Splunk ile AI Destekli Siber Savunma ve Tehdit Avc\u0131l\u0131\u011f\u0131 - Morten<\/title>\n<meta name=\"description\" content=\"Geleneksel a\u011f y\u00f6netiminden yaz\u0131l\u0131m tan\u0131ml\u0131 a\u011flara ge\u00e7i\u015f. 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