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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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Intrusion detection in network systems using transformer based approachThe growing complexity of modern network infrastructures, driven by cloud computing, IoT, and 5G, poses significant challenges for traditional Intrusion Detection Systems (IDS), which often fail to... Author: Ngo Hoa Thi Keyword: Transformer Intrusion Detection Cybersecurity Network Traffic Deep Learning Anomaly Detection
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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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