Review on approaches of federated modeling in anomaly-based intrusion detection for IoT devices

UA Isma'ila, KU Danyaro, AA Muazu… - IEEE Access, 2024 - ieeexplore.ieee.org
The novelty of Federated Learning (FL) has emerged as a promising alternative to
centralized machine learning systems in the context of anomaly-based intrusion detection …

An explainable multi-modal model for advanced cyber-attack detection in industrial control systems

S Bahadoripour, H Karimipour, AN Jahromi, A Islam - Internet of Things, 2024 - Elsevier
Abstract The convergence of Industrial Control Systems (ICS) and intelligent Internet of
Things (IoT) technologies has rendered ICS more vulnerable to a growing range of cyber …

Resource-efficient federated learning over IoAT for rice leaf disease classification

M Aggarwal, V Khullar, N Goyal, TA Prola - Computers and Electronics in …, 2024 - Elsevier
Rice is an important staple food in Asia. It is produced and consumed in large quantities. It
contributes to 15% of protein intake and 21% of total per capita energy intake in the region …

[HTML][HTML] Privacy-Preserving Federated Learning-Based Intrusion Detection Technique for Cyber-Physical Systems

SA Mahmud, N Islam, Z Islam, Z Rahman, ST Mehedi - Mathematics, 2024 - mdpi.com
The Internet of Things (IoT) has revolutionized various industries, but the increased
dependence on all kinds of IoT devices and the sensitive nature of the data accumulated by …

Federated Learning–Based Model to Lightweight IDSs for heterogeneous IoT Networks: State-of-the-Art, Challenges and Future Directions.

S Alsaleh, MEB Menai, S Al-Ahmadi - IEEE Access, 2024 - ieeexplore.ieee.org
A large number of Internet of Things (IoT) devices have been deployed in numerous
applications (eg, smart homes, healthcare, smart grids, manufacturing processes, and …

[HTML][HTML] Federated multi-label learning (FMLL): Innovative method for classification tasks in animal science

B Ghasemkhani, O Varliklar, Y Dogan, S Utku… - Animals, 2024 - mdpi.com
Simple Summary This study addresses the classification task in animal science, which helps
organize and analyze complex data, essential for making informed decisions. It introduces …

Landscape of machine learning evolution: privacy-preserving federated learning frameworks and tools

G Nguyen, J Sáinz-Pardo Díaz, A Calatrava… - Artificial Intelligence …, 2024 - Springer
Abstract Machine learning is one of the most widely used technologies in the field of Artificial
Intelligence. As machine learning applications become increasingly ubiquitous, concerns …

[HTML][HTML] Energy-Efficient Federated Learning for Internet of Things: Leveraging In-Network Processing and Hierarchical Clustering

M Baqer - Future Internet, 2024 - mdpi.com
Federated learning (FL) has emerged as a promising solution for the Internet of Things (IoT),
facilitating distributed artificial intelligence while ensuring communication efficiency and data …

Federated learning for multi-institutional on 3D brain tumor segmentation

YM Elbachir, D Makhlouf, G Mohamed… - … on Pattern Analysis …, 2024 - ieeexplore.ieee.org
Accurate segmentation of brain tumours images is crucial for diagnosis, treatment planning,
and monitoring of disease progression. However, acquiring sufficient medical imaging data …

Edge Computing Enabled Anomaly Detection in IoT Environments Using Federated Learning

V Kansal, SO Husain, R Kumar… - 2024 International …, 2024 - ieeexplore.ieee.org
This research explores the integration of edge computing and unified learning procedures
for peculiarity locations in Internet of Things (IoT) situations. Four inconsistency discovery …