{"id":476627,"date":"2023-08-09T07:31:20","date_gmt":"2023-08-09T07:31:20","guid":{"rendered":""},"modified":"2024-05-31T05:34:30","modified_gmt":"2024-05-31T05:34:30","slug":"data-diddling","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/data-diddling\/","title":{"rendered":"Veri Hilesi"},"content":{"rendered":"

Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131, bu verilere dayanan bireyleri veya sistemleri aldatmak veya yan\u0131ltmak amac\u0131yla verileri de\u011fi\u015ftirme, tadil etme veya tahrif etme gibi k\u00f6t\u00fc niyetli eylemleri ifade eder. Bu aldat\u0131c\u0131 uygulaman\u0131n mali kay\u0131plar, itibar kayb\u0131 ve g\u00fcvenlik ihlalleri gibi ciddi sonu\u00e7lar\u0131 olabilir. Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 finans, sa\u011fl\u0131k hizmetleri, e-ticaret ve daha fazlas\u0131 gibi \u00e7e\u015fitli alanlarda ger\u00e7ekle\u015febilir. Bir proxy sunucu sa\u011flay\u0131c\u0131s\u0131 olarak OneProxy (oneproxy.pro), m\u00fc\u015fterilerini potansiyel risklerden ve g\u00fcvenlik a\u00e7\u0131klar\u0131ndan korumak i\u00e7in veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131n\u0131 anlaman\u0131n \u00f6nemini kabul eder.<\/p>\n

Veri Doland\u0131r\u0131c\u0131l\u0131\u011f\u0131n\u0131n k\u00f6keninin tarihi ve bundan ilk s\u00f6z<\/h2>\n

Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 kavram\u0131n\u0131n k\u00f6keni, bilgi i\u015flem ve veri i\u015flemenin ilk g\u00fcnlerine kadar uzanabilir. Ancak 1970'lerde bilgisayarlar\u0131n i\u015fletmelerde ve devlet kurumlar\u0131nda daha yayg\u0131n hale gelmesiyle b\u00fcy\u00fck ilgi g\u00f6rd\u00fc. "Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131" teriminin kendisi hile yapmak, aldatmak veya manip\u00fcle etmek anlam\u0131na gelen "diddle" s\u00f6zc\u00fc\u011f\u00fcnden kaynaklanm\u0131\u015f olabilir. Dijital veriler ve bilgisayar sistemleri geli\u015ftik\u00e7e veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 teknikleri ve y\u00f6ntemleri de geli\u015fti.<\/p>\n

Veri Doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 hakk\u0131nda detayl\u0131 bilgi<\/h2>\n

Veri hilesi, verilerin hemen fark edilemeyecek \u015fekilde kas\u0131tl\u0131 olarak de\u011fi\u015ftirilmesini i\u00e7erir ve bu da veriler i\u015flenirken veya analiz edilirken yanl\u0131\u015f veya yan\u0131lt\u0131c\u0131 sonu\u00e7lara yol a\u00e7ar. Bu aldat\u0131c\u0131 uygulama a\u015fa\u011f\u0131daki gibi \u00e7e\u015fitli y\u00f6ntemlerle ger\u00e7ekle\u015ftirilebilir:<\/p>\n

    \n
  1. Yetkisiz Eri\u015fim<\/strong>: Hassas bilgileri de\u011fi\u015ftirmek i\u00e7in bir sisteme veya veritaban\u0131na yetkisiz eri\u015fim elde etmek.<\/li>\n
  2. SQL Enjeksiyonu<\/strong>: K\u00f6t\u00fc ama\u00e7l\u0131 SQL sorgular\u0131 eklemek ve verileri de\u011fi\u015ftirmek i\u00e7in web uygulamalar\u0131ndaki g\u00fcvenlik a\u00e7\u0131klar\u0131ndan yararlanmak.<\/li>\n
  3. Truva atlar\u0131<\/strong>: \u0130\u015fleme s\u0131ras\u0131nda verileri de\u011fi\u015ftiren k\u00f6t\u00fc ama\u00e7l\u0131 kodun sisteme sokulmas\u0131.<\/li>\n
  4. Veri Ele Ge\u00e7irme<\/strong>: Aktar\u0131lan verileri yakalamak ve hedefine ula\u015fmadan \u00f6nce de\u011fi\u015ftirmek.<\/li>\n
  5. Sahtecilik<\/strong>: Bir veri k\u00fcmesine yanl\u0131\u015f veri olu\u015fturma ve ekleme.<\/li>\n
  6. Zamana Dayal\u0131 Sald\u0131r\u0131lar<\/strong>: Tespitten ka\u00e7\u0131nmak i\u00e7in belirli zamanlarda verileri de\u011fi\u015ftirmek.<\/li>\n<\/ol>\n

    Data Diddle'\u0131n i\u00e7 yap\u0131s\u0131 ve nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131<\/h2>\n

    Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131, bir sistem i\u00e7inde veri giri\u015fi, i\u015fleme, depolama ve alma dahil olmak \u00fczere \u00e7e\u015fitli a\u015famalarda ger\u00e7ekle\u015febilir. Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131n\u0131n i\u00e7 yap\u0131s\u0131 birka\u00e7 ad\u0131mdan olu\u015fur:<\/p>\n

      \n
    1. G\u00fcvenlik A\u00e7\u0131klar\u0131n\u0131 Belirleme<\/strong>: Sald\u0131rgan, hedef sistem veya uygulamadaki veri manip\u00fclasyonu i\u00e7in kullan\u0131labilecek g\u00fcvenlik a\u00e7\u0131klar\u0131n\u0131 belirler.<\/li>\n
    2. Eri\u015fim Kazanmak<\/strong>: Sald\u0131rgan, yaz\u0131l\u0131m a\u00e7\u0131klar\u0131ndan yararlanarak veya \u00e7al\u0131nan kimlik bilgilerini kullanarak sisteme veya veritaban\u0131na yetkisiz eri\u015fim elde eder.<\/li>\n
    3. Verileri De\u011fi\u015ftirme<\/strong>: Sald\u0131rgan sisteme girdikten sonra \u015f\u00fcphe yaratmadan verileri ama\u00e7lar\u0131na g\u00f6re de\u011fi\u015ftirir.<\/li>\n
    4. \u0130zleri Gizlemek<\/strong>: Sald\u0131rgan, tespit edilmekten ka\u00e7\u0131nmak i\u00e7in izlerini silmeye ve veri manip\u00fclasyonuna ili\u015fkin her t\u00fcrl\u00fc kan\u0131t\u0131 silmeye \u00e7al\u0131\u015f\u0131r.<\/li>\n<\/ol>\n

      Veri Doland\u0131r\u0131c\u0131l\u0131\u011f\u0131n\u0131n temel \u00f6zelliklerinin analizi<\/h2>\n

      Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131, onu di\u011fer siber sald\u0131r\u0131 ve veri manip\u00fclasyonu bi\u00e7imlerinden ay\u0131ran birka\u00e7 temel \u00f6zellik sergiliyor:<\/p>\n

        \n
      1. Gizlilik<\/strong>: Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131, sald\u0131rganlar\u0131n k\u00f6t\u00fc ama\u00e7l\u0131 faaliyetlerine fark edilmeden devam etmelerine olanak tan\u0131yacak \u015fekilde incelikli ve tespit edilmesi zor olacak \u015fekilde tasarlanm\u0131\u015ft\u0131r.<\/li>\n
      2. Kesinlik<\/strong>: Verilerde yap\u0131lan de\u011fi\u015fiklikler genellikle kesindir ve iyi hesaplanm\u0131\u015ft\u0131r; \u015f\u00fcphe uyand\u0131rmadan belirli sonu\u00e7lara ula\u015fmay\u0131 ama\u00e7lamaktad\u0131r.<\/li>\n
      3. Hedeflenen<\/strong>: Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 sald\u0131r\u0131lar\u0131 genellikle belirli bireyleri, kurulu\u015flar\u0131 veya sistemleri hedef al\u0131r.<\/li>\n
      4. Geli\u015fen Teknikler<\/strong>: Siber g\u00fcvenlik \u00f6nlemleri ilerledik\u00e7e veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 teknikleri de geli\u015fiyor, bu da etkili bir \u015fekilde m\u00fccadele etmeyi zorla\u015ft\u0131r\u0131yor.<\/li>\n<\/ol>\n

        Veri Hilesi T\u00fcrleri<\/h2>\n

        Veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 \u00e7e\u015fitli teknikleri ve y\u00f6ntemleri kapsar; bunlardan baz\u0131lar\u0131 \u015funlard\u0131r:<\/p>\n\n\n\n\n\n\n\n\n\n
        Tip<\/th>\nTan\u0131m<\/th>\n<\/tr>\n<\/thead>\n
        Zamana Dayal\u0131 Veri Hilesi<\/td>\n\u0130stenilen sonu\u00e7lar\u0131 elde etmek i\u00e7in verileri belirli zamanlarda de\u011fi\u015ftirmek.<\/td>\n<\/tr>\n
        Giri\u015f Verileriyle Oynamak<\/td>\n\u0130\u015fleme ve analiz sonu\u00e7lar\u0131n\u0131 de\u011fi\u015ftirmek i\u00e7in giri\u015f a\u015famas\u0131nda verileri de\u011fi\u015ftirmek.<\/td>\n<\/tr>\n
        \u00c7\u0131kt\u0131 Verileriyle Oynamak<\/td>\nYan\u0131lt\u0131c\u0131 bilgi g\u00f6r\u00fcnt\u00fclemek i\u00e7in \u00e7\u0131kt\u0131 a\u015famas\u0131nda verilere m\u00fcdahale edilmesi.<\/td>\n<\/tr>\n
        Veritaban\u0131 Verileri Doland\u0131r\u0131c\u0131l\u0131\u011f\u0131<\/td>\nSonraki i\u015flemleri etkilemek i\u00e7in do\u011frudan veritaban\u0131ndaki verileri de\u011fi\u015ftirmek.<\/td>\n<\/tr>\n
        Uygulama D\u00fczeyinde Veri Kar\u0131\u015ft\u0131rma<\/td>\nVerileri i\u015flemek i\u00e7in uygulamalardaki g\u00fcvenlik a\u00e7\u0131klar\u0131ndan yararlanmak.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Veri Hilesi'ni kullanma yollar\u0131, sorunlar ve \u00e7\u00f6z\u00fcmleri<\/h2>\n

        Veri Hilesi'ni kullanma yollar\u0131<\/h3>\n

        Veri hilesi \u00e7e\u015fitli \u015fekillerde k\u00f6t\u00fcye kullan\u0131labilir:<\/p>\n

          \n
        1. Finansal doland\u0131r\u0131c\u0131l\u0131k<\/strong>: Doland\u0131r\u0131c\u0131l\u0131k veya zimmete para ge\u00e7irmeyi kolayla\u015ft\u0131rmak i\u00e7in mali verileri de\u011fi\u015ftirmek.<\/li>\n
        2. Akademik Hile<\/strong>: Adil olmayan avantajlar elde etmek i\u00e7in akademik kay\u0131tlar\u0131 veya test sonu\u00e7lar\u0131n\u0131 de\u011fi\u015ftirmek.<\/li>\n
        3. Se\u00e7imde Tahrifat<\/strong>: Se\u00e7im sonu\u00e7lar\u0131n\u0131 etkilemek amac\u0131yla oylama verilerinin tahrif edilmesi.<\/li>\n<\/ol>\n

          Veri Hilesi kullan\u0131m\u0131na ili\u015fkin sorunlar ve \u00e7\u00f6z\u00fcmleri<\/h3>\n
            \n
          1. Veri B\u00fct\u00fcnl\u00fc\u011f\u00fc Kontrolleri<\/strong>: D\u00fczenli veri b\u00fct\u00fcnl\u00fc\u011f\u00fc kontrolleri ve sa\u011flama toplamlar\u0131 uygulamak, veri hilesinden kaynaklanan tutars\u0131zl\u0131klar\u0131n belirlenmesine yard\u0131mc\u0131 olabilir.<\/li>\n
          2. Giri\u015f kontrolu<\/strong>: Kritik sistemlere ve verilere eri\u015fimin k\u0131s\u0131tlanmas\u0131, yetkisiz manip\u00fclasyonu \u00f6nleyebilir.<\/li>\n
          3. Denetim Yollar\u0131<\/strong>: Kapsaml\u0131 denetim izlerinin s\u00fcrd\u00fcr\u00fclmesi, \u015f\u00fcpheli etkinliklerin ve veri de\u011fi\u015fikliklerinin tespit edilmesine olanak tan\u0131r.<\/li>\n<\/ol>\n

            Ana \u00f6zellikler ve benzer terimlerle di\u011fer kar\u015f\u0131la\u015ft\u0131rmalar<\/h2>\n\n\n\n\n\n\n\n\n
            Terim<\/th>\nTan\u0131m<\/th>\n<\/tr>\n<\/thead>\n
            Verilerin De\u011fi\u015ftirilmesi<\/td>\nYetkisiz veri de\u011fi\u015fiklikleri i\u00e7in genel terim.<\/td>\n<\/tr>\n
            Veri Manip\u00fclasyonu<\/td>\nVerileri me\u015fru ama\u00e7larla de\u011fi\u015ftirmek.<\/td>\n<\/tr>\n
            Veri Sahtekarl\u0131\u011f\u0131<\/td>\nSistemleri veya kullan\u0131c\u0131lar\u0131 aldatmak i\u00e7in verileri tahrif etmek.<\/td>\n<\/tr>\n
            Veri Ele Ge\u00e7irme<\/td>\nAktar\u0131m halindeki verileri manip\u00fclasyon olmadan yakalama.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

            Veri Hilesi ile ilgili gelece\u011fin perspektifleri ve teknolojileri<\/h2>\n

            Teknoloji ilerledik\u00e7e veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 teknikleri de geli\u015fecek. Veri hilesi ile ili\u015fkili riskleri azaltmak i\u00e7in a\u015fa\u011f\u0131daki konularda ilerlemeler beklenmektedir:<\/p>\n

              \n
            1. Anormallik Tespiti i\u00e7in Yapay Zeka (AI)<\/strong>: Yapay zeka destekli sistemler, veri hilesinden kaynaklanan anormal veri kal\u0131plar\u0131n\u0131n belirlenmesine yard\u0131mc\u0131 olabilir.<\/li>\n
            2. Blockchain Teknolojisi<\/strong>: Blockchain'in merkezi olmayan yap\u0131s\u0131 veri b\u00fct\u00fcnl\u00fc\u011f\u00fcn\u00fc art\u0131rabilir ve yetkisiz de\u011fi\u015fiklikleri \u00f6nleyebilir.<\/li>\n
            3. Geli\u015fmi\u015f \u015eifreleme<\/strong>: G\u00fc\u00e7l\u00fc \u015fifreleme y\u00f6ntemleri, verileri m\u00fcdahaleye ve manip\u00fclasyona kar\u015f\u0131 koruyabilir.<\/li>\n<\/ol>\n

              Proxy sunucular\u0131 nas\u0131l kullan\u0131labilir veya Veri Hilesi ile nas\u0131l ili\u015fkilendirilebilir?<\/h2>\n

              Proxy sunucular\u0131, kullan\u0131c\u0131lar ve internet aras\u0131nda arac\u0131 g\u00f6revi g\u00f6rd\u00fcklerinden veri doland\u0131r\u0131c\u0131l\u0131\u011f\u0131nda rol oynayabilir. Baz\u0131 durumlarda sald\u0131rganlar kimliklerini gizlemek i\u00e7in proxy sunucular\u0131 kullanabilir ve bu da veri manip\u00fclasyonu giri\u015fimlerinin kayna\u011f\u0131n\u0131n izlenmesini zorla\u015ft\u0131rabilir. OneProxy (oneproxy.pro), k\u00f6t\u00fc niyetli akt\u00f6rlerin k\u00f6t\u00fcye kullan\u0131m\u0131n\u0131 \u00f6nlemek i\u00e7in g\u00fcvenli ve g\u00fcvenilir proxy hizmetlerinin \u00f6nemini vurgulamaktad\u0131r.<\/p>\n

              \u0130lgili Ba\u011flant\u0131lar<\/h2>\n

              Veri Doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 ve siber g\u00fcvenlik hakk\u0131nda daha fazla bilgi i\u00e7in a\u015fa\u011f\u0131daki kaynaklar\u0131 inceleyebilirsiniz:<\/p>\n

                \n
              1. Siber G\u00fcvenlik ve Altyap\u0131 G\u00fcvenli\u011fi Ajans\u0131 (CISA)<\/a><\/li>\n
              2. Ulusal Standartlar ve Teknoloji Enstit\u00fcs\u00fc (NIST)<\/a><\/li>\n
              3. A\u00e7\u0131k Web Uygulama G\u00fcvenli\u011fi Projesi (OWASP)<\/a><\/li>\n<\/ol>\n

                Bilgi sahibi olman\u0131n ve sa\u011flam g\u00fcvenlik \u00f6nlemleri alman\u0131n, verileri korumak ve veri hilesi tehditlerine kar\u015f\u0131 koruma sa\u011flamak i\u00e7in \u00e7ok \u00f6nemli oldu\u011funu unutmay\u0131n.<\/p>","protected":false},"featured_media":505451,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476627","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Data Diddling: An Overview<\/mark>","faq_items":[{"question":"What is Data Diddling?","answer":"Data diddling refers to the malicious act of altering, modifying, or falsifying data with the intent to deceive or mislead individuals or systems that rely on that data. This deceptive practice can have severe consequences, including financial losses, reputational damage, and security breaches."},{"question":"How did Data Diddling originate?","answer":"The concept of data diddling can be traced back to the early days of computing and data processing, gaining significant attention in the 1970s with the rise of computers in businesses and government agencies."},{"question":"How does Data Diddling work?","answer":"Data diddling involves several steps, starting with identifying vulnerabilities in the target system, gaining unauthorized access, manipulating the data, and concealing traces to avoid detection."},{"question":"What are the key features of Data Diddling?","answer":"Data diddling is characterized by its stealth, precision, targeted nature, and evolving techniques to evade detection and continue malicious activities."},{"question":"What are the types of Data Diddling?","answer":"Various types of data diddling include time-based data diddling, input and output data diddling, database data diddling, and application-level data diddling."},{"question":"How can Data Diddling be misused?","answer":"Data diddling can be misused for financial fraud, academic cheating, election tampering, and other deceptive purposes."},{"question":"What are the problems related to Data Diddling, and how can they be solved?","answer":"The problems associated with data diddling can be addressed through data integrity checks, access control measures, and maintaining comprehensive audit trails."},{"question":"How does Data Diddling compare to other terms like Data Tampering and Data Spoofing?","answer":"Data diddling is a specific form of unauthorized data alteration, while data tampering and data spoofing are broader terms related to manipulating data for various purposes."},{"question":"What are the future perspectives and technologies related to Data Diddling?","answer":"The future holds advancements in AI-powered anomaly detection, blockchain for enhanced data integrity, and stronger encryption to combat data diddling."},{"question":"How can proxy servers be associated with Data Diddling?","answer":"Proxy servers can be misused by attackers to obfuscate their identity and carry out data diddling attempts."}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476627","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":2,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476627\/revisions"}],"predecessor-version":[{"id":505453,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476627\/revisions\/505453"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/505451"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=476627"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}