A comprehensive review of the state-of-the-art on security and privacy issues in healthcare
Currently, healthcare is critical environment in our society, which attracts attention to
malicious activities and has caused an important number of damaging attacks. In parallel …
malicious activities and has caused an important number of damaging attacks. In parallel …
Balancing QoS and security in the edge: Existing practices, challenges, and 6G opportunities with machine learning
While the emerging 6G networks are anticipated to meet the high-end service quality
demands of the mobile edge users in terms of data rate and delay satisfaction, new attack …
demands of the mobile edge users in terms of data rate and delay satisfaction, new attack …
[HTML][HTML] Federated learning for malware detection in IoT devices
Billions of IoT devices lacking proper security mechanisms have been manufactured and
deployed for the last years, and more will come with the development of Beyond 5G …
deployed for the last years, and more will come with the development of Beyond 5G …
Boosting-based DDoS detection in internet of things systems
Distributed Denial-of-Service (DDoS) attacks remain challenging to mitigate in the existing
systems, including in-home networks that comprise different Internet of Things (IoT) devices …
systems, including in-home networks that comprise different Internet of Things (IoT) devices …
A survey of public IoT datasets for network security research
Publicly available datasets are an indispensable tool for researchers, as they allow testing
new algorithms on a wide range of different scenarios and making scientific experiments …
new algorithms on a wide range of different scenarios and making scientific experiments …
Intelligent and behavioral-based detection of malware in IoT spectrum sensors
Abstract The number of Cyber-Physical Systems (CPS) available in industrial environments
is growing mainly due to the evolution of the Internet-of-Things (IoT) paradigm. In such a …
is growing mainly due to the evolution of the Internet-of-Things (IoT) paradigm. In such a …
[HTML][HTML] Fedstellar: A platform for decentralized federated learning
Abstract In 2016, Google proposed Federated Learning (FL) as a novel paradigm to train
Machine Learning (ML) models across the participants of a federation while preserving data …
Machine Learning (ML) models across the participants of a federation while preserving data …
Artificial intelligence assisted nanogenerator applications
Piezoelectric and triboelectric nanogenerators are at the forefront of converting ambient
mechanical energy into electricity. These devices have experienced significant …
mechanical energy into electricity. These devices have experienced significant …
[HTML][HTML] Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring
Abstract The application of Deep Neural Networks (DNNs) for monitoring cyberattacks in
Internet of Things (IoT) systems has gained significant attention in recent years. However …
Internet of Things (IoT) systems has gained significant attention in recent years. However …
A survey of smart home iot device classification using machine learning-based network traffic analysis
Smart home IoT devices lack proper security, raising safety and privacy concerns. One-size-
fits-all network administration is ineffective because of the diverse QoS requirements of IoT …
fits-all network administration is ineffective because of the diverse QoS requirements of IoT …