Federated learning for privacy preservation in smart healthcare systems: A comprehensive survey
Recent advances in electronic devices and communication infrastructure have
revolutionized the traditional healthcare system into a smart healthcare system by using …
revolutionized the traditional healthcare system into a smart healthcare system by using …
Deep learning for cybersecurity in smart grids: Review and perspectives
Protecting cybersecurity is a non‐negotiable task for smart grids (SG) and has garnered
significant attention in recent years. The application of artificial intelligence (AI), particularly …
significant attention in recent years. The application of artificial intelligence (AI), particularly …
Detection of false data injection attacks in smart grid: A secure federated deep learning approach
As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber
attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one …
attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one …
[HTML][HTML] FL-PMI: federated learning-based person movement identification through wearable devices in smart healthcare systems
Recent technological developments, such as the Internet of Things (IoT), artificial
intelligence, edge, and cloud computing, have paved the way in transforming traditional …
intelligence, edge, and cloud computing, have paved the way in transforming traditional …
[HTML][HTML] An optimized model for network intrusion detection systems in industry 4.0 using XAI based Bi-LSTM framework
S Sivamohan, SS Sridhar - Neural Computing and Applications, 2023 - Springer
Industry 4.0 enable novel business cases, such as client-specific production, real-time
monitoring of process condition and progress, independent decision making and remote …
monitoring of process condition and progress, independent decision making and remote …
Federated continuous learning based on stacked broad learning system assisted by digital twin networks: An incremental learning approach for intrusion detection in …
The edge of the Internet of Things (IoT), which consists of unmanned aerial vehicles (UAVs),
is vulnerable to network intrusion because software and wireless connections are used …
is vulnerable to network intrusion because software and wireless connections are used …
A novel experience-driven and federated intelligent threat-defense framework in IoMT
The Artificial Intelligence-enabled Internet of Medical Things (AI-IoMT) envisions the
connectivity of medical devices encompassing advanced computing technologies to …
connectivity of medical devices encompassing advanced computing technologies to …
Efficient and lightweight convolutional networks for iot malware detection: A federated learning approach
Over the past few years, billions of unsecured Internet of Things (IoT) devices have been
produced and released, and that number will only grow as wireless technology advances …
produced and released, and that number will only grow as wireless technology advances …
Intrusion Detection based on Federated Learning: a systematic review
JL Hernandez-Ramos, G Karopoulos… - arXiv preprint arXiv …, 2023 - arxiv.org
The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
[PDF][PDF] Secure and Reliable Designs for Intrusion Detection Methods Developed Utilizing Artificial Intelligence Approaches
VV Vegesna - International Journal of Current Engineering and …, 2023 - researchgate.net
Intrusion detection system plays an important role in network security. Intrusion detection
model is a predictive model used to predict the network data traffic as normal or intrusion …
model is a predictive model used to predict the network data traffic as normal or intrusion …