[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …
threatening. Network intrusion detection has been widely accepted as an effective method to …
A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges
A Khraisat, A Alazab - Cybersecurity, 2021 - Springer
Abstract The Internet of Things (IoT) has been rapidly evolving towards making a greater
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
A bidirectional LSTM deep learning approach for intrusion detection
The rise in computer networks and internet attacks has become alarming for most service
providers. It has triggered the need for the development and implementation of intrusion …
providers. It has triggered the need for the development and implementation of intrusion …
Ai-driven cybersecurity: an overview, security intelligence modeling and research directions
Artificial intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (or
Industry 4.0), which can be used for the protection of Internet-connected systems from cyber …
Industry 4.0), which can be used for the protection of Internet-connected systems from cyber …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
Cybersecurity data science: an overview from machine learning perspective
In a computing context, cybersecurity is undergoing massive shifts in technology and its
operations in recent days, and data science is driving the change. Extracting security …
operations in recent days, and data science is driving the change. Extracting security …
Survey of intrusion detection systems: techniques, datasets and challenges
Cyber-attacks are becoming more sophisticated and thereby presenting increasing
challenges in accurately detecting intrusions. Failure to prevent the intrusions could degrade …
challenges in accurately detecting intrusions. Failure to prevent the intrusions could degrade …
CNN-based network intrusion detection against denial-of-service attacks
As cyberattacks become more intelligent, it is challenging to detect advanced attacks in a
variety of fields including industry, national defense, and healthcare. Traditional intrusion …
variety of fields including industry, national defense, and healthcare. Traditional intrusion …
A detailed investigation and analysis of using machine learning techniques for intrusion detection
P Mishra, V Varadharajan… - … surveys & tutorials, 2018 - ieeexplore.ieee.org
Intrusion detection is one of the important security problems in todays cyber world. A
significant number of techniques have been developed which are based on machine …
significant number of techniques have been developed which are based on machine …
Deep learning approach combining sparse autoencoder with SVM for network intrusion detection
M Al-Qatf, Y Lasheng, M Al-Habib, K Al-Sabahi - Ieee Access, 2018 - ieeexplore.ieee.org
Network intrusion detection systems (NIDSs) provide a better solution to network security
than other traditional network defense technologies, such as firewall systems. The success …
than other traditional network defense technologies, such as firewall systems. The success …