ÇİZGE SİNİR AĞLARI: GÖREVLER, BİLGİ GÜVENLİĞİ, SİBER GÜVENLİK VE ADLİ BİLİŞİM

Öz

Çizge Sinir Ağları (Graph Neural Networks-GNN), Yapay Sinir Ağları (Artificial Neural Networks-ANN) ailesine mensup ve çizgeler üzerinden bilgi çıkarımı işlemi gerçekleştiren bir derin öğrenme yöntemidir. Bilgi güvenliği teknikleri ise sistem ve insan olarak adlandırabileceğimiz varlığın tehdit ve tehlike oluşturmasına karşı bilginin gizliliği, bütünlüğü ve erişimine yönelik korumayı amaçlamaktadır. Siber güvenlik açısından ise, GNN’ler kritik altyapılara yönelik saldırıları önlemek ve tespit etmek için kullanılır. Kritik altyapıların ve sistemlerin saldırganlar tarafından ilgi odağı ve maddi-manevi kayıp kazancı sayesinde önem kazanmaktadır. Bu çalışmada GNN’lerin görevleri ve temel kullanım alanları ile birlikte bilgi güvenliği, siber güvenlik ve adli bilişim konularına yönelik gelişmeleri açıklanmaktadır.

Anahtar Kelimeler

• Çizge Sinir Ağları
• Yapay Sinir Ağları
• Bilgi Güvenliği
• Siber Güvenlik
• Adli Bilişim

GRAPH NEURAL NETWORKS: TASKS, INFORMATION SECURITY, CYBER SECURITY, AND DIGITAL FORENSICS

Öz

Graph Neural Networks (GNN) is a deep learning method that belongs to the Artificial Neural Networks (ANN) family and performs information extraction over graphs. Information security techniques aim to protect the confidentiality, integrity, and access of information against threats and dangers posed by systems and human beings. In terms of cyber security, GNNs are used to prevent and detect attacks on critical infrastructures. Critical infrastructures and systems are gaining importance due to the focus of attention by attackers and the gain in financial and moral losses. In this study, the tasks and main usage areas of GNNs and their developments in information security, cyber security, and digital forensics are explained.

Anahtar Kelimeler

• Graph Neural Networks
• Artificial Neural Networks
• Information Security
• Cyber Security
• Digital Forensics

Kaynakça

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