[HTML][HTML] A machine learning-based intrusion detection for detecting internet of things network attacks
Abstract The Internet of Things (IoT) refers to the collection of all those devices that could
connect to the Internet to collect and share data. The introduction of varied devices …
connect to the Internet to collect and share data. The introduction of varied devices …
Metamorphic malware and obfuscation: a survey of techniques, variants, and generation kits
K Brezinski, K Ferens - Security and Communication Networks, 2023 - Wiley Online Library
The competing landscape between malware authors and security analysts is an ever‐
changing battlefield over who can innovate over the other. While security analysts are …
changing battlefield over who can innovate over the other. While security analysts are …
Artificial intelligence algorithm-based economic denial of sustainability attack detection systems: Cloud computing environments
THH Aldhyani, H Alkahtani - Sensors, 2022 - mdpi.com
Cloud computing is currently the most cost-effective means of providing commercial and
consumer IT services online. However, it is prone to new flaws. An economic denial of …
consumer IT services online. However, it is prone to new flaws. An economic denial of …
Botnet attack detection in iot using machine learning
There are an increasing number of Internet of Things (IoT) devices connected to the network
these days, and due to the advancement in technology, the security threads and …
these days, and due to the advancement in technology, the security threads and …
The influence of salp swarm algorithm-based feature selection on network anomaly intrusion detection
A Alsaleh, W Binsaeedan - IEEE Access, 2021 - ieeexplore.ieee.org
Network security plays a critical role in our lives because of the threats and attacks to which
we are exposed, which are increasing daily; these attacks result in a need to develop …
we are exposed, which are increasing daily; these attacks result in a need to develop …
Intrusion detection for softwarized networks with semi-supervised federated learning
With the increasing development of 5G/Beyond 5G and network softwarization techniques,
we have more flexibility and agility in the network. This can be exploited by Machine …
we have more flexibility and agility in the network. This can be exploited by Machine …
A lightweight intelligent network intrusion detection system using one-class autoencoder and ensemble learning for IoT
W Yao, L Hu, Y Hou, X Li - Sensors, 2023 - mdpi.com
Network intrusion detection technology is key to cybersecurity regarding the Internet of
Things (IoT). The traditional intrusion detection system targeting Binary or Multi …
Things (IoT). The traditional intrusion detection system targeting Binary or Multi …
An approach for the application of a dynamic multi-class classifier for network intrusion detection systems
Currently, the use of machine learning models for developing intrusion detection systems is
a technology trend which improvement has been proven. These intelligent systems are …
a technology trend which improvement has been proven. These intelligent systems are …
A collaborative DNN-based low-latency IDPS for mission-critical smart factory networks
Industrial Control Systems (ICSs) have entered an era of modernization enabled by the
recent progress in Information Technologies (IT), particularly the Industrial Internet of Things …
recent progress in Information Technologies (IT), particularly the Industrial Internet of Things …
Machine learning techniques for network-based intrusion detection system: a survey paper
LAH Ahmed, YAM Hamad - 2021 National Computing Colleges …, 2021 - ieeexplore.ieee.org
The rapid growth of Internet technologies and further dependence on online services,
increase the demand for keeping these networks and data secure. The protection of online …
increase the demand for keeping these networks and data secure. The protection of online …