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dc.contributor.advisorCan, Ahmet Burak
dc.contributor.authorTürker, Sercan
dc.date.accessioned2019-10-21T12:06:35Z
dc.date.issued2019
dc.date.submitted2019-06-14
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dc.identifier.urihttp://hdl.handle.net/11655/9309
dc.description.abstractAs the popularity of Android mobile operating system grows, the number of software developed to harm the users of this system increases. Therefore, many studies have been done to detect malicious Android software. Apart from the classification of Android software as malicious or benign, classification of the malicious software into their families is also very important in terms of the security of the Android operating system. In this study, a machine learning based classification system is developed that analyzes malicious Android software and estimates the family of them. The developed system detects the requested permissions and API calls of the malicious Android software and uses them as features in machine learning algorithms to classify malwares. The performance of the system is investigated using various data sets and the evaluation results show that all classification algorithms classified the malware with a high accuracy. In addition to this work, a study of detecting an unknown malware which belongs to a family that had never seen before is made and these unknown malwares are classified with a high success rate.tr_TR
dc.language.isoturtr_TR
dc.publisherFen Bilimleri Enstitüsütr_TR
dc.rightsinfo:eu-repo/semantics/openAccesstr_TR
dc.subjectMakine öğrenmesi
dc.subjectZararlı android yazılımları
dc.subjectStatik analiz
dc.subjectZararlı yazılım ailelerine göre sınıflandırma
dc.subject.lcshKonu Başlıkları Listesi::Teknoloji. Mühendisliktr_TR
dc.titleZararlı Android Yazılımlarının Makine Öğrenmesi ile Ailelerine Göre Sınıflandırılmasıtr_TR
dc.title.alternativeAndroid Malware Family Classification with Machine Learningtr_TR
dc.typemasterThesistr_TR
dc.description.ozetAndroid mobil işletim sisteminin oldukça popüler olması bu sistemin kullanıcılarına zarar vermek amacıyla geliştirilen yazılımların sayısında artışa sebep olmaktadır. Bu nedenle zararlı Android yazılımlarının tespit edilmesi amacıyla birçok çalışma yapılmıştır. Android yazılımlarının zararlı ya da zararsız olarak sınıflandırılması dışında, zararlı olduğu bilinen yazılımların ait oldukları ailelere göre sınıflandırılması da Android işletim sisteminin güvenliği kapsamında oldukça önemlidir. Bu çalışmada zararlı Android yazılımlarını analiz ederek bu yazılımların ait olduğu aileyi tahmin eden makine öğrenmesi tabanlı bir sistem geliştirilmiştir. Geliştirilen bu sistem, zararlı Android yazılımlarının talep ettiği izinleri ve yaptığı API çağrılarını tespit ederek bunları makine öğrenmesi algoritmalarında öznitelik olarak kullanmakta ve farklı sınıflandırma algoritmaları ile zararlı yazılımların sınıflandırılmasına imkan tanımaktadır. Sistemin performansı çeşitli veri kümelerinde yapılan deneylerle incelenmiş ve deney sonuçlarında tüm sınıflandırma algoritmalarının zararlı yazılımları yüksek doğruluk değerleriyle sınıflandırdığı görülmüştür. Bu çalışmaya ek olarak, daha önce karşılaşılmamış bir zararlı yazılım ailesine ait zararlı yazılımın bilinmeyen olarak tespit edilebilmesi için de çalışma yapılmış ve bu yazılımlar yüksek oranda başarıyla tespit edilmiştir.tr_TR
dc.contributor.departmentBilgisayar Mühendisliğitr_TR
dc.embargo.termsAcik erisimtr_TR
dc.embargo.lift2019-10-21T12:06:35Z


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