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Evolutionary machine learning: A survey
Evolutionary Computation (EC) approaches are inspired by nature and solve optimization
problems in a stochastic manner. They can offer a reliable and effective approach to address …
problems in a stochastic manner. They can offer a reliable and effective approach to address …
Learning-based methods for cyber attacks detection in IoT systems: A survey on methods, analysis, and future prospects
Internet of Things (IoT) is a develo** technology that provides the simplicity and benefits of
exchanging data with other devices using the cloud or wireless networks. However, the …
exchanging data with other devices using the cloud or wireless networks. However, the …
Anomaly-based intrusion detection systems in iot using deep learning: A systematic literature review
The Internet of Things (IoT) concept has emerged to improve people's lives by providing a
wide range of smart and connected devices and applications in several domains, such as …
wide range of smart and connected devices and applications in several domains, such as …
Internet of things: Evolution, concerns and security challenges
The escalated growth of the Internet of Things (IoT) has started to reform and reshape our
lives. The deployment of a large number of objects adhered to the internet has unlocked the …
lives. The deployment of a large number of objects adhered to the internet has unlocked the …
A systematic review on Deep Learning approaches for IoT security
The constant spread of smart devices in many aspects of our daily life goes hand in hand
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
Towards secure intrusion detection systems using deep learning techniques: Comprehensive analysis and review
Providing a high-performance Intrusion Detection System (IDS) can be very effective in
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
A novel intrusion detection framework for optimizing IoT security
The emerging expanding scope of the Internet of Things (IoT) necessitates robust intrusion
detection systems (IDS) to mitigate security risks effectively. However, existing approaches …
detection systems (IDS) to mitigate security risks effectively. However, existing approaches …
A multi-stage classification approach for iot intrusion detection based on clustering with oversampling
Intrusion detection of IoT-based data is a hot topic and has received a lot of interests from
researchers and practitioners since the security of IoT networks is crucial. Both supervised …
researchers and practitioners since the security of IoT networks is crucial. Both supervised …
Industrial IoT intrusion detection via evolutionary cost-sensitive learning and fog computing
Cyber attacks and intrusions have become the major obstacles to the adoption of the
Industrial Internet of Things (IIoT) in critical industries. Imbalanced data distribution is a …
Industrial Internet of Things (IIoT) in critical industries. Imbalanced data distribution is a …
Research on unsupervised feature learning for android malware detection based on restricted Boltzmann machines
Android malware detection has attracted much attention in recent years. Existing methods
mainly research on extracting static or dynamic features from mobile apps and build mobile …
mainly research on extracting static or dynamic features from mobile apps and build mobile …