17 papers
Deep Learning-Driven Friendly Jamming for Secure Multicarrier ISAC Under Channel Uncertainty
Bui Minh Tuan, Van-Dinh Nguyen, Diep N. Nguyen +5
Integrated sensing and communication (ISAC) systems promise efficient spectrum utilization by jointly supporting radar sensing and wireless communication. This paper presents a dee…
Carpe Diem: Critical Learning Period-Aware Contract-Based Incentives for Federated Learning
Thanh Linh Nguyen, Dinh Thai Hoang, Diep N. Nguyen +1
Critical learning periods (CLPs) in federated learning (FL) refer to early stages during which low-quality contributions (e.g., sparse training data availability) can permanently i…
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…
Efficient STAR-RIS Mode for Energy Minimization in WPT-FL Networks with NOMA
MohammadHossien Alishahi, Ming Zeng, Paul Fortier +5
With the massive deployment of IoT devices in 6G networks, several critical challenges have emerged, such as large communication overhead, coverage limitations, and limited battery…
"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…