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Applying transformer architecture to enhance attack detection performance in intrusion detection systemsIntrusion Detection Systems (IDS) are crucial in safeguarding network security against increasingly sophisticated threats. In this study, we propose a Transformer-based intrusion detection model to... Author: Vu Phuong Thi, Ha Hoang Thi Hong, Truong Dinh Gia, Yen Tran Thi Keyword: Intrusion Detection Transformer UNSW-NB15 Cybersecurity Self-attention
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An effective malware classification method based on byte-to-image transformation and integration of the vision transformer modelMalware classification is a critical problem in cybersecurity, characterized by numerous challenges due to the complexity and diversity of malware variants. In this study, we propose a novel approach... Author: Thuy Nguyen Thi Thu, Linh Do Thi Hong, Ha Hoang Thi Hong, Cuc Pham Thi, Binh Pham Anh Keyword: Malware Classification Vision Transformer (ViT) Bytecode Image Representation Deep Learning Self-Attention
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