This paper focuses on proposing a network intrusion detection model applying fundamental machine learning techniques to enhance early detection of network intrusions (rapid detection of attack...

Author: Phuong Hoang Thi

Keyword: Network attack DDoS machine learning deep learning dimensionality reduction

In the field of image processing, recognition is one of the major challenges for researchers in recent years. The goal of recognition is to detect and extract features in images to classify samples...

Author: Dương Đình Tú, Phan Xuan Hieu, Hoang Tuan Hiep

Keyword: self-driving robot car; image processing; Convolutional Neural Network; deep learning.

Sentiment analysis is a critical job in natural language processing. Controlling and evaluating customer feedback on their goods is a task that companies are especially interested in. For reading...

Author: Huế Lương Thị Minh

Keyword: Natural language processing; LSTM; deep learning; machine learning; BiDAF.

This study addresses the challenge of effectively detecting phishing email campaigns that exhibit increasingly sophisticated and sequential behaviors. The primary objective is to develop a detection...

Author: Hien Dang Thi, Duyen Tran Thi

Keyword: Phishing detection email security temporal analysis transformer models multi-email sequence analysis BiLSTM urgency score suspicious score

This study focuses on predicting product rating scores from customer text feedback. This task combines the challenges of natural language processing (NLP) with the class imbalance phenomenon commonly...

Author: Ha Dien Thi Hong

Keyword: Product rating prediction customer text feedback natural language processing (NLP) machine learning models model performance evaluation

Writing is a core skill in English as a Foreign Language (EFL) learning, requiring learners to develop accuracy, coherence, and critical reflection. This study investigates the attitudes and...

Author: Phan Lam Thi

Keyword: Self-assessment Peer-assessment Writing skills Learner attitudes

Flying ad hoc networks (FANETs) in 6G environments require routing schemes that can cope with rapid topology changes, limited UAV energy resources, and unstable air-to-air links. This paper proposes a...

Author: Nguyen Thu Thi

Keyword: 6G-enabled FANETs Spatio temporal graph learning Risk sensitive deep reinforcement learning Propulsion aware routing Route survival probability

In the era of digital transformation, alongside the rapid devel-opment of the Internet and online applications, phishing at-tacks targeting users through malicious URLs have been in-creasingly...

Author: Mai Dang Thi

Keyword: URL Phishing detection Autoencoder latent space

Detecting polymorphic and zero-day malware remains a significant challenge due to the high similarity in characteristics between malicious variants and benign files, which reduces the effectiveness of...

Author: Mai Dang Thi, Hien Dinh Cong

Keyword: Malware detection Image-based malware analysis deep learning Triplet Loss zero-day malware

This paper proposes a GNN-enhanced multi-agent deep reinforcement learning framework for antijamming routing in mobile ad hoc networks. The approach combines temporal graph representations with...

Author: Hanh Vu My, Oanh Le Thi Kieu

Keyword: MANET Anti-jamming Graph Neural Networks (GNN) Multi-Agent Reinforcement Learning (MARL) Adversarial Learning