7 papers
Multiple-Input Auto-Encoder Guided Feature Selection for IoT Intrusion Detection Systems
Phai Vu Dinh, Diep N. Nguyen, Dinh Thai Hoang +3
While intrusion detection systems (IDSs) benefit from the diversity and generalization of IoT data features, the data diversity (e.g., the heterogeneity and high dimensions of data…
A New Class of Analog Precoding for Multi-Antenna Multi-User Communications over High-Frequency Bands
W. Zhu, H. D. Tuan, E. Dutkiewicz +2
A network relying on a large antenna-array-aided base station is designed for delivering multiple information streams to multi-antenna users over high-frequency bands such as the m…
Holographic Multi-User Multi-Stream Beamforming Maintaining Rate-Fairness
W. Zhu, H. D. Tuan, E. Dutkiewicz +2
We present the first investigation into the transmission of multi-stream information from a base station equipped with reconfigurable holographic surfaces (RHS) to multiple users w…
"Security for Everyone" in Finite Blocklength IRS-aided Systems With Perfect and Imperfect CSI
Monir Abughalwa, Diep N. Nguyen, Dinh Thai Hoang +4
Provisioning secrecy for all users, given the heterogeneity in their channel conditions, locations, and the unknown location of the attacker/eavesdropper, is challenging and not al…
Secure Communications for All Users in Low-Resolution IRS-aided Systems Under Imperfect and Unknown CSI
Monir Abughalwa, Diep N. Nguyen, Dinh Thai Hoang +3
Provisioning secrecy for all users, given the heterogeneity and uncertainty of their channel conditions, locations, and the unknown location of the attacker/eavesdropper, is challe…
Teacher-free Latent Self-distillation and Class-separable Representations for Lightweight IoT Attack Detection
Phai Vu Dinh, Quang Uy Nguyen, Thai Hoang Dinh +6
Knowledge distillation (KD) has been widely used to improve lightweight AI models by transferring soft-label knowledge from a large teacher model to a student model. However, exist…