Kimlik Hırsızı Web Sitelerinin Farklı DeepLearning4J Modelleri ile Performanslarının Karşılaştırılması

Yıl 2021, Sayı: 28, 425 - 431, 30.11.2021

Özlem Batur Dinler Canan Batur Şahin Laith Abualigah

https://doi.org/10.31590/ejosat.1004778

Öz

İlk olarak 2019’da Çin’in Wuhan şehrinde görülen yeni tip koranavirüs (COVID-19 ) hastalığı nedeniyle 11 Mart 2020 tarihinde Dünya Sağlık Örgütü (DSÖ) tarafından pandemi ilan edilmiştir. Dünya genelinde hâlâ etkisi devam etmekte olan bu salgın, kısa sürede tüm dünya toplumunun gündelik yaşam aktivitelerini ve alışkanlıklarını hızlı bir şekilde değiştirerek digital ortam uygulamalarına doğru kaydırmıştır. Bu doğrultuda, artan siber saldırı atakları ve yaşanan veri ihlalleri salgın toplumu için büyük bir risk oluşturmuştur. Bu bağlamda, dijital ortam uygulamalarının güvenliği COVID-19 salgını ile çok daha önemli bir sorun haline gelmiştir. Bu sorun özellikle kimlik hırsızı web siteleri üzerinde gözlenmiştir. Web kimlik hırsızlığı, güvenilir kurumları taklit ederek kişilerin ad, soyad, şifre ve kredi kartı numaraları gibi kişisel bilgileri çalma yöntemidir. Bu, bilginin ifşa olmasına ve mali zarara neden olacaktır. Çalışmanın odağı, kimlik hırsızı web sitelerinin tanımlanması amacı ile kullanılan birkaç DeepLearning4j (DL4j) modeline dayanmaktadır. Bununla birlikte, çalışmanın temel amacı, değerlendirme metriklerinin performanslarını iyileştirmek amacı ile DeepLearning4J (DL4J) modellerinin etkinliğini verimli bir şekilde izlemektir.

Anahtar Kelimeler

COVID-19, DL4J, Siber Saldırı, Web, Kimlik Hırsızlığı.

Comparison of Performance of Phishing Web Sites with Different DeepLearning4J Models

Öz

Due to the new type of coronavirus (COVID-19) disease, which was first seen in Wuhan, China in 2019, a pandemic was declared by the World Health Organization (WHO) on March 11, 2020. The pandemic, which is still in effect throughout the world, has changed the daily life activities and habits of the whole world community in a short time and shifted them towards digital media applications. Accordingly, increasing cyber-attack attacks and data breaches have created great risk for the pandemic society. In this context, the security of digital media applications has become a much more important issue with the COVID-19 outbreak. The issue has been observed especially on phishing websites. Web phishing is the practice of stealing personal information such as name, last name, password, and credit card numbers of individuals by imitating a reputable business. It will result in the exposure of information and the financial damage. The focus of the study is based on several DeepLearning4j (DL4j) models used to identify phishing websites. However, the main purpose of the study is to efficiently monitor the effectiveness of DeepLearning4J (DL4J) models with the aim of improving the performance of evaluation metrics.

Anahtar Kelimeler

COVID-19, DL4J, Cyber attack, Web, Phishing

Kaynakça

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