A Review of blockchain technology in knowledge-defined networking, its application, benefits, and challenges

PADSN Wijesekara, S Gunawardena - Network, 2023 - mdpi.com
Knowledge-Defined Networking (KDN) necessarily consists of a knowledge plane for the
generation of knowledge, typically using machine learning techniques, and the …

“why should i trust your ids?”: An explainable deep learning framework for intrusion detection systems in internet of things networks

Z Abou El Houda, B Brik… - IEEE Open Journal of the …, 2022 - ieeexplore.ieee.org
Internet of Things (IoT) is an emerging paradigm that is turning and revolutionizing
worldwide cities into smart cities. However, this emergence is accompanied with several …

Mitfed: A privacy preserving collaborative network attack mitigation framework based on federated learning using sdn and blockchain

Z Abou El Houda, AS Hafid… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Distributed denial-of-service (DDoS) attacks continue to grow at a rapid rate plaguing
Internet Service Providers (ISPs) and individuals in a stealthy way. Thus, intrusion detection …

Cochain-SC: An intra-and inter-domain DDoS mitigation scheme based on blockchain using SDN and smart contract

Z Abou El Houda, AS Hafid, L Khoukhi - IEEE Access, 2019 - ieeexplore.ieee.org
With the exponential growth in the number of insecure devices, the impact of Distributed
Denial-of-Service (DDoS) attacks is growing rapidly. Existing DDoS mitigation schemes are …

A survey of Blockchain technologies applied to software‐defined networking: Research challenges and solutions

H Nam Nguyen, H Anh Tran, S Fowler… - IET Wireless Sensor …, 2021 - Wiley Online Library
Abstract Software‐Defined Networking (SDN) brought a groundbreaking idea to facilitate
network system management by decoupling and abstracting the Control plane and Data …

When collaborative federated learning meets blockchain to preserve privacy in healthcare

Z Abou El Houda, AS Hafid… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Data-driven Machine and Deep Learning (ML/DL) is an emerging approach that uses
medical data to build robust and accurate ML/DL models that can improve clinical decisions …

Bringing intelligence to software defined networks: Mitigating DDoS attacks

Z Abou El Houda, L Khoukhi… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
As one of the most devastating types of Distributed Denial of Service (DDoS) attacks,
Domain Name System (DNS) amplification attack represents a big threat and one of the …

Computation offloading in blockchain-enabled MCS systems: A scalable deep reinforcement learning approach

Z Chen, J Zhang, Z Huang, P Wang, Z Yu… - Future Generation …, 2024 - Elsevier
Abstract In Mobile Crowdsensing (MCS) systems, cloud service providers (CSPs) pay for
and analyze the sensing data collected by mobile devices (MDs) to enhance the Quality-of …

Ensemble learning for intrusion detection in SDN-based zero touch smart grid systems

Z Abou El Houda, B Brik… - 2022 IEEE 47th …, 2022 - ieeexplore.ieee.org
Software-defined network (SDN) is widely deployed on Smart Grid (SG) systems. It consists
in decoupling control and data planes, to automate the monitoring and management of the …

Towards a secure and reliable federated learning using blockchain

H Moudoud, S Cherkaoui… - 2021 IEEE Global …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a distributed machine learning (ML) technique that enables
collaborative training in which devices perform learning using a local dataset while …