Review of the Methods Used for the Detection of Spam Email

Yıl 2020, Cilt: 11 Sayı: 3, 977 - 987, 30.09.2020

Ersin Enes Eryılmaz Erdal Kılıç

https://doi.org/10.24012/dumf.715638

Cited By: 2

Öz

In this study, the methods in the literature for filtering spam emails were reviewed. Emails are actively used by people or communities who want to make propaganda, advertising, phishing because of their ease of use and low cost. People or communities who want to achieve their goals send unnecessary and unsolicited mail to the email accounts they never knew. These mails cause serious financial and moral damages to internet users and also engage in internet traffic. Unsolicited emails are a method that is sent to the recipient without his consent and that is generally used by malicious or promotional purposes. In this article, important developments in spam filtering methods are evaluated and deficiencies are revealed. The filtering of spam emails has been reviewed under two main headings: non-artificial intelligence-based and artificial intelligence-based. It has been observed that non-artificial intelligence-based methods give effective results in detecting spam, but there is spam that can easily skip these methods. It has been revealed that systems based on artificial intelligence are frequently used in spam detection and research and development are in this direction. In recent years, with the development of artificial intelligence, machine learning and algorithms emerging in its deep learning field, which is a sub-branch of it, have been detected with high performance and spam email detection. Due to the high performance of machine learning and deep learning methods for filtering spam emails, studies in this field are concentrated in detecting and filtering spam email.

Anahtar Kelimeler

spam email detection, artificial intelligence, machine learning

İstenmeyen Epostaların Tespiti için Kullanılan Yöntemlerin İncelenmesi

Öz

İstenmeyen elektronik postalar alıcıya rızası dışında gönderilen ve genellikle kötü niyetli veya tanıtım amaçlı olan kişilerin başvurduğu bir yöntemdir. Elektronik postalar, kullanımının kolaylığı, maliyetlerinin ucuz olmasından dolayı propaganda, reklam, oltalama yapmak isteyen kişi veya topluluklar tarafından etkin bir biçimde kullanılmaktadır. Amaçlarını gerçekleştirmek isteyen kişi veya topluluklar hiç tanımadıkları e-posta hesaplarına gereksiz ve istenmeyen postalar gönderirler. Bu çalışmada, istenmeyen elektronik postaların filtrelenmesi için literatürde bulunan yöntemler incelenmiştir. Bu istenmeyen e-posta filtreleme yöntemleri temel olarak yapay zekâ tabanlı olmayan ve yapay zekâ tabanlı olan şeklinde iki ana başlık altında incelenmiştir. Yapay zekâ tabanlı olmayan yöntemlerin istenmeyen e-posta tespitinde etkili sonuçlar verdiği ancak literatürde bu yöntemleri atlayabilen tekniklerin olduğu görülmektedir. İstenmeyen e-posta tespitinde yapay zekâ tabanlı makine öğrenmesi algoritmaları kullanan sistemlerin popülaritesinin arttığı ve araştırmaların bu yönde ivme kazandığı görülmektedir. Özellikle derin öğrenme yöntemleri yüksek performansları nedeniyle spam tespitinde tercih edilmeye başlamıştır. Literatürde klasik makine öğrenme yöntemlerinden olan Bayes, Destek Vektör Makinesi, Yapay Sinir Ağı, Rastgele Orman, Çok Katmanlı Algılayıcı, K-En Yakın Komşu gibi algoritmalarının kullanıldığı spam tespit yöntemlerinde yüksek başarım sağladığı görülmektedir. Uzun Kısa Süreli Bellek ve Evrişimsel Sinir Ağı algoritmalarını kullanan derin öğrenme temelli spam tespit yöntemlerinin başarım oranlarını daha da artırdığı farklı veri kümeleri kullanılarak gösterilmiştir. Ayrıca spam tespit sistemlerinde bulunan açık problemler ve Türkçe özelinde bu çalışmaların hangi aşamada olduğu da bu çalışmada irdelenmiştir ve çeşitli öneriler yapılmıştır.

Anahtar Kelimeler

İstenmeyen eposta tespiti, yapay zeka, makine öğrenmesi, derin öğrenme

Kaynakça

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