Joint power cost and latency minimization for secure collaborative learning system
Tác giả: Nguyen Thi Thanh Van, Vu Van Quang, Nguyen Cong LuongTóm tắt:
This work investigates the model update security in a collaborative learning or federated learning network by using the covert communication. The CC uses the jamming signal and multiple friendly jammers (FJs) are deployed that can offer jamming services to the model owner, i.e., a base station (BS). To enable the BS to select the best FJ, i.e., the lowest cost FJ, a truthful auction is adopted. Then, a problem is formulated to optimize the jamming power, transmission power, and local accuracy. The objective is to minimize the training latency, subject to the security performance requirement and budget of the BS. To solve the non-convex problem, we adopt a Successive Convex Approximation algorithm. The simulation results reveals some interesting things. For example, the trustful auction reduces the jamming cost of the BS as the number of FJs increases.
- Predicting the rate of hydrogen cyanide emission from surface water into the air : a critical review
- A multilevel image thresholding approach using history-based adaptive differential Evolution with linear population size reduction algorithm
- Nghiên cứu than sinh học từ thực vật xâm hại để xử lý thuốc nhuộm trong môi trường nước
- The effect of HCN emissions from tailing storage facilities of a gold mine on public health : findings from a major case study in Thailand
- Về sự không tồn tại nghiệm của một bất đẳng thức parabolic





