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FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in
  Industrial IoT

FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT

11 December 2020
J. Li
Lingjuan Lyu
X. Liu
X. Zhang
X. Lyu
ArXivPDFHTML

Papers citing "FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT"

12 / 12 papers shown
Title
Anomaly-Flow: A Multi-domain Federated Generative Adversarial Network for Distributed Denial-of-Service Detection
Anomaly-Flow: A Multi-domain Federated Generative Adversarial Network for Distributed Denial-of-Service Detection
Leonardo Henrique de Melo
G. Bertoli
Michele Nogueira
A. Santos
Lourenço Alves Pereira Junior
53
0
0
18 Mar 2025
Multi-Model based Federated Learning Against Model Poisoning Attack: A
  Deep Learning Based Model Selection for MEC Systems
Multi-Model based Federated Learning Against Model Poisoning Attack: A Deep Learning Based Model Selection for MEC Systems
Somayeh Kianpisheh
Chafika Benzaid
T. Taleb
FedML
AAML
16
0
0
12 Sep 2024
CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Community
CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Community
Yan Liu
Bin Guo
Nuo Li
Yasan Ding
Zhouyangzi Zhang
Zhiwen Yu
50
1
0
09 Jul 2024
Collaborative Policy Learning for Dynamic Scheduling Tasks in
  Cloud-Edge-Terminal IoT Networks Using Federated Reinforcement Learning
Collaborative Policy Learning for Dynamic Scheduling Tasks in Cloud-Edge-Terminal IoT Networks Using Federated Reinforcement Learning
Do-Yup Kim
Dami Lee
Ji-Wan Kim
Hyun-Suk Lee
28
4
0
02 Jul 2023
Decentralized Online Federated G-Network Learning for Lightweight
  Intrusion Detection
Decentralized Online Federated G-Network Learning for Lightweight Intrusion Detection
Mert Nakıp
Baran Can Gül
Erol Gelenbe
19
8
0
22 Jun 2023
Evaluating Federated Learning for Intrusion Detection in Internet of
  Things: Review and Challenges
Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges
Enrique Mármol Campos
Pablo Fernández Saura
Aurora González-Vidal
José Luis Hernández Ramos
Jorge Bernal Bernabé
G. Baldini
A. Gómez-Skarmeta
38
149
0
02 Aug 2021
Too Expensive to Attack: Enlarge the Attack Expense through Joint
  Defense at the Edge
Too Expensive to Attack: Enlarge the Attack Expense through Joint Defense at the Edge
Jianhua Li
Ximeng Liu
Jiong Jin
Shui Yu
AAML
13
3
0
03 Jul 2021
Federated Learning for Intrusion Detection System: Concepts, Challenges
  and Future Directions
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions
Shaashwat Agrawal
Sagnik Sarkar
Ons Aouedi
Gokul Yenduri
Kandaraj Piamrat
S. Bhattacharya
Praveen Kumar Reddy Maddikunta
Thippa Reddy Gadekallu
19
231
0
16 Jun 2021
Privacy-preserving Federated Learning based on Multi-key Homomorphic
  Encryption
Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption
Jing Ma
Si-Ahmed Naas
S. Sigg
X. Lyu
29
243
0
14 Apr 2021
Too Expensive to Attack: A Joint Defense Framework to Mitigate
  Distributed Attacks for the Internet of Things Grid
Too Expensive to Attack: A Joint Defense Framework to Mitigate Distributed Attacks for the Internet of Things Grid
Jianhua Li
Ximeng Liu
Jiong Jin
Shui Yu
AAML
14
2
0
01 Apr 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu
Han Yu
Xingjun Ma
Chen Chen
Lichao Sun
Jun Zhao
Qiang Yang
Philip S. Yu
FedML
183
355
0
07 Dec 2020
Threats to Federated Learning: A Survey
Threats to Federated Learning: A Survey
Lingjuan Lyu
Han Yu
Qiang Yang
FedML
202
434
0
04 Mar 2020
1