A survey on security threats and defensive techniques of machine learning: A data driven view
Machine learning is one of the most prevailing techniques in computer science, and it has
been widely applied in image processing, natural language processing, pattern recognition …
been widely applied in image processing, natural language processing, pattern recognition …
A highly accurate deep learning based approach for developing wireless sensor network middleware
RA Alshinina, KM Elleithy - IEEE Access, 2018 - ieeexplore.ieee.org
Despite the popularity of wireless sensor networks (WSNs) in a wide range of applications,
security problems associated with them have not been completely resolved. Middleware is …
security problems associated with them have not been completely resolved. Middleware is …
Machine Learning-Based DoS Attack Detection Techniques in Wireless Sensor Network: A Review
In diverse areas, the wireless sensor network (WSN) has an important role to play and has
its application in various domains. Even though WSN has become very popular in recent …
its application in various domains. Even though WSN has become very popular in recent …
Machine learning to combat cyberattack: a survey of datasets and challenges
The ever-increasing number of multi-vector cyberattacks has become a concern for all levels
of organizations. Attackers are infecting Internet-enabled devices and exploiting them to …
of organizations. Attackers are infecting Internet-enabled devices and exploiting them to …
A hybrid deep random neural network for cyberattack detection in the industrial internet of things
The Industrial Internet of Things (IIoT) refers to the use of traditional Internet of Things (IoT)
concepts in industrial sectors and applications. IIoT has several applications in smart homes …
concepts in industrial sectors and applications. IIoT has several applications in smart homes …
An extensive survey on intrusion detection systems: Datasets and challenges for modern scenario
Cyberattacks are becoming more and more advanced, making it more difficult to identity
suspicious activities on network traffic. Weaponizing the data in the line between network …
suspicious activities on network traffic. Weaponizing the data in the line between network …
Security in wireless sensor networks: Attacks and evasion
SA Jilani, C Koner, S Nandi - 2020 National conference on …, 2020 - ieeexplore.ieee.org
Wireless Sensor network is a typical research area, where energy efficiency is a key issue. It
is popular due to low cost solution and real world problem solving features. WSN is also very …
is popular due to low cost solution and real world problem solving features. WSN is also very …
Malicious node detection in wireless sensor network using swarm intelligence optimization
N Al-Maslamani, M Abdallah - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Over the last few years, modern technology has emerged rapidly in almost every aspect of
our lives. In the field of wireless communication and the Internet of Things (IoT), Wireless …
our lives. In the field of wireless communication and the Internet of Things (IoT), Wireless …
A deep reinforcement learning based intrusion detection system (drl-ids) for securing wireless sensor networks and internet of things
H Benaddi, K Ibrahimi, A Benslimane… - Wireless Internet: 12th EAI …, 2020 - Springer
Many modern infrastructures incorporate a number of sensors and actuators interconnected
via wireless links using Wireless Sensor Network (WSN) and Internet of Things (IoT) …
via wireless links using Wireless Sensor Network (WSN) and Internet of Things (IoT) …
Anomaly detection using machine learning techniques in wireless sensor networks
S Ifzarne, H Tabbaa, I Hafidi… - Journal of Physics …, 2021 - iopscience.iop.org
The number of Wireless sensor network (WSN) deployments have been growing so
exponentially over the recent years. Due to their small size and cost-effective, WSN are …
exponentially over the recent years. Due to their small size and cost-effective, WSN are …