47 citations · 79 across the 13 of their papers we have counts for
14 papers
Federated Learning based on Defending Against Data Poisoning Attacks in IoT
Jiayin Li, Wenzhong Guo, Xingshuo Han +2
The rapidly expanding number of Internet of Things (IoT) devices is generating huge quantities of data, but the data privacy and security exposure in IoT devices, especially in the…
Evolution as a Service: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization
Bowen Zhao, Wei-Neng Chen, Feng-Feng Wei +3
Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer an elegant way to handle combinatorial optimization problems (COPs). However, limited by expertise and reso…
Backdoor Defense with Machine Unlearning
Yang Liu, Mingyuan Fan, Cen Chen +4
Backdoor injection attack is an emerging threat to the security of neural networks, however, there still exist limited effective defense methods against the attack. In this paper,…
Too Expensive to Attack: Enlarge the Attack Expense through Joint Defense at the Edge
Jianhua Li, Ximeng Liu, Jiong JIn +1
The distributed denial of service (DDoS) attack is detrimental to businesses and individuals as people are heavily relying on the Internet. Due to remarkable profits, crackers favo…
Too Expensive to Attack: A Joint Defense Framework to Mitigate Distributed Attacks for the Internet of Things Grid
Jianhua Li, Ximeng Liu, Jiong Jin +1
The distributed denial of service (DDoS) attack is detrimental to businesses and individuals as we are heavily relying on the Internet. Due to remarkable profits, crackers favor DD…
Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud
Zhuoran Ma, Jianfeng Ma, Yinbin Miao +3
Federated learning has become prevalent in medical diagnosis due to its effectiveness in training a federated model among multiple health institutions (i.e. Data Islands (DIs)). Ho…