[HTML][HTML] Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …
installed in residential buildings. If leveraged properly, that data could assist end-users …
A review on machine learning and deep learning perspectives of IDS for IoT: recent updates, security issues, and challenges
Abstract Internet of Things (IoT) is widely accepted technology in both industrial as well as
academic field. The objective of IoT is to combine the physical environment with the cyber …
academic field. The objective of IoT is to combine the physical environment with the cyber …
A survey on IoT intrusion detection: Federated learning, game theory, social psychology, and explainable AI as future directions
In the past several years, the world has witnessed an acute surge in the production and
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
State-of-the-art in artificial neural network applications: A survey
This is a survey of neural network applications in the real-world scenario. It provides a
taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of …
taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of …
A survey of machine and deep learning methods for internet of things (IoT) security
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest developing fields in …
one another with minimal human intervention. IoT is one of the fastest developing fields in …
Building an efficient intrusion detection system based on feature selection and ensemble classifier
Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …
to safeguard the integrity and availability of sensitive assets in the protected systems …
A review of intrusion detection systems using machine and deep learning in internet of things: Challenges, solutions and future directions
The Internet of Things (IoT) is poised to impact several aspects of our lives with its fast
proliferation in many areas such as wearable devices, smart sensors and home appliances …
proliferation in many areas such as wearable devices, smart sensors and home appliances …
Cyberattacks detection in iot-based smart city applications using machine learning techniques
In recent years, the widespread deployment of the Internet of Things (IoT) applications has
contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies …
contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies …
Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation
Intrusion detection systems (IDSs) are intrinsically linked to a comprehensive solution of
cyberattacks prevention instruments. To achieve a higher detection rate, the ability to design …
cyberattacks prevention instruments. To achieve a higher detection rate, the ability to design …
Machine-learning-assisted security and privacy provisioning for edge computing: A survey
S Singh, R Sulthana, T Shewale… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Edge computing (EC), is a technological game changer that has the ability to connect
millions of sensors and provide services at the device end. The broad vision of EC integrates …
millions of sensors and provide services at the device end. The broad vision of EC integrates …