3 citations · 18 across the 20 of their papers we have counts for
6 papers · 1 filter
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach
Kai Li, Jingjing Zheng, Xin Yuan +3
This paper proposes a novel, data-agnostic, model poisoning attack on Federated Learning (FL), by designing a new adversarial graph autoencoder (GAE)-based framework. The attack re…
From OTFS to DD-ISAC: Integrating Sensing and Communications in the Delay Doppler Domain
Weijie Yuan, Lin Zhou, Saeid K. Dehkordi +4
Next-generation vehicular networks are expected to provide the capability of robust environmental sensing in addition to reliable communications to meet intelligence requirements.…
Federated Learning via Active RIS Assisted Over-the-Air Computation
Deyou Zhang, Ming Xiao, Mikael Skoglund +1
In this paper, we propose leveraging the active reconfigurable intelligence surface (RIS) to support reliable gradient aggregation for over-the-air computation (AirComp) enabled fe…
Charge Manipulation Attacks Against Smart Electric Vehicle Charging Stations and Deep Learning-based Detection Mechanisms
Hamidreza Jahangir, Subhash Lakshminarayana, H. Vincent Poor
The widespread deployment of "smart" electric vehicle charging stations (EVCSs) will be a key step toward achieving green transportation. The connectivity features of smart EVCSs c…
IRS Assisted Federated Learning A Broadband Over-the-Air Aggregation Approach
Deyou Zhang, Ming Xiao, Zhibo Pang +2
We consider a broadband over-the-air computation empowered model aggregation approach for wireless federated learning (FL) systems and propose to leverage an intelligent reflecting…
Adversarial Learning for Implicit Semantic-Aware Communications
Zhimin Lu, Yong Xiao, Zijian Sun +5
Semantic communication is a novel communication paradigm that focuses on recognizing and delivering the desired meaning of messages to the destination users. Most existing works in…