One-Class Classification for Anomaly Detection with Kernel Density Estimation and Genetic Programming. - Van Loi Cao; Miguel Nicolau; James McDermott (EuroGP, 2016)

Improving Fitness Functions in Genetic Programming for Classification on Unbalanced Credit Card Data. - Van Loi Cao; Nhien-An Le-Khac; Michael O'Neill 001; Miguel Nicolau; James McDermott (EvoApplications (1), 2016)

Collective Anomaly Detection Based on Long Short-Term Memory Recurrent Neural Networks. - Loïc Bontemps; Van Loi Cao; James McDermott; Nhien-An Le-Khac (FDSE, 2016)

A Hybrid Autoencoder and Density Estimation Model for Anomaly Detection. - Van Loi Cao; Miguel Nicolau; James McDermott (PPSN, 2016)

Late-acceptance and step-counting hill-climbing GP for anomaly detection. - Van Loi Cao; Miguel Nicolau; James McDermott (GECCO (Companion), 2017)

Collective Anomaly Detection based on Long Short Term Memory Recurrent Neural Network. - Loïc Bontemps; Van Loi Cao; James McDermott; Nhien-An Le-Khac (CoRR, 2017)

Improving Fitness Functions in Genetic Programming for Classification on Unbalanced Credit Card Datasets. - Van Loi Cao; Nhien-An Le-Khac; Miguel Nicolau; Michael O'Neill 001; James McDermott (CoRR, 2017)

One-Class Collective Anomaly Detection Based on LSTM-RNNs. - Nga Nguyen Thi; Van Loi Cao; Nhien-An Le-Khac (Trans. Large Scale Data Knowl. Centered Syst., 2017)

Semantics Based Substituting Technique for Reducing Code Bloat in Genetic Programming. - Thi Huong Chu; Quang Uy Nguyen; Van Loi Cao (SoICT, 2018)

One-class Collective Anomaly Detection based on Long Short-Term Memory Recurrent Neural Networks. - Nga Nguyen Thi; Van Loi Cao; Nhien-An Le-Khac (CoRR, 2018)

Learning Latent Distribution for Distinguishing Network Traffic in Intrusion Detection System. - Ly Vu; Van Loi Cao; Quang Uy Nguyen; Diep N. Nguyen; Dinh Thai Hoang; Eryk Dutkiewicz (ICC, 2019)

A Clustering-based Shrink AutoEncoder for Detecting Anomalies in Intrusion Detection Systems. - Cong Thanh Bui; Van Loi Cao; Minh Hoang; Quang Uy Nguyen (KSE, 2019)

Learning Neural Representations for Network Anomaly Detection. - Van Loi Cao; Miguel Nicolau; James McDermott (IEEE Trans. Cybern., 2019)

Clustering-Based Deep Autoencoders for Network Anomaly Detection. - Van Quan Nguyen; Viet Hung Nguyen; Nhien-An Le-Khac; Van Loi Cao (FDSE, 2020)

Feature Representation of AutoEncoders for Unsupervised IoT Malware Detection. - Huu Noi Nguyen; Van Cuong Nguyen; Nguyen Ngoc Tran; Van Loi Cao (FDSE, 2021)

Automatically Estimate Clusters in Autoencoder-based Clustering Model for Anomaly Detection. - Van Quan Nguyen; Viet Hung Nguyen; Nhien-An Le-Khac; Van Loi Cao (RIVF, 2021)

Denoising Latent Representation with SOMs for Unsupervised IoT Malware Detection. - Huu Noi Nguyen; Nguyen Ngoc Tran; Tuan Hao Hoang; Van Loi Cao (SN Comput. Sci., 2022)

Learning Latent Representation for IoT Anomaly Detection. - Ly Vu; Van Loi Cao; Quang Uy Nguyen; Diep N. Nguyen; Dinh Thai Hoang; Eryk Dutkiewicz (IEEE Trans. Cybern., 2022)

Deep Clustering Based Latent Representation for IoT Malware Detection. - Huu Noi Nguyen; Nguyen Ngoc Tran; Van Loi Cao (ICCAIS, 2023)

Few-Shot Learning with Discriminative Representation for Cyberattack Detection. - Van Loi Cao; Manh Tuan Nguyen; Trang Dang Le Dinh (KSE, 2023)

Graphish: Advanced Phishing URL Detection via Graph-Based Embeddings. - Van Hoan Do; Thi Le Vuong; Van Loi Cao; Thi Phuong Lan Tran; Tien Dung Pham; Van Dinh Bui (KSE, 2024)

Reliable Pilot Search Method for Enhancing BER Performance in Underwater Acoustic OFDM Systems with MMSE Estimator. - Nga Nguyen Thi; Anh Huy Phan 003; Van Loi Cao; Pham Thanh Hiep (Int. J. Wirel. Inf. Networks, 2024)