[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 …
Artificial intelligence, cyber-threats and Industry 4.0: Challenges and opportunities
This survey paper discusses opportunities and threats of using artificial intelligence (AI)
technology in the manufacturing sector with consideration for offensive and defensive uses …
technology in the manufacturing sector with consideration for offensive and defensive uses …
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 …
Deep learning approach for intelligent intrusion detection system
Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …
A scheme for generating a dataset for anomalous activity detection in iot networks
The exponential growth of the Internet of Things (IoT) devices provides a large attack surface
for intruders to launch more destructive cyber-attacks. The intruder aimed to exhaust the …
for intruders to launch more destructive cyber-attacks. The intruder aimed to exhaust the …
A review of tabular data synthesis using GANs on an IDS dataset
Recent technological innovations along with the vast amount of available data worldwide
have led to the rise of cyberattacks against network systems. Intrusion Detection Systems …
have led to the rise of cyberattacks against network systems. Intrusion Detection Systems …
Shallow and deep networks intrusion detection system: A taxonomy and survey
Intrusion detection has attracted a considerable interest from researchers and industries.
The community, after many years of research, still faces the problem of building reliable and …
The community, after many years of research, still faces the problem of building reliable and …
Evaluation of machine learning classifiers for mobile malware detection
Mobile devices have become a significant part of people's lives, leading to an increasing
number of users involved with such technology. The rising number of users invites hackers …
number of users involved with such technology. The rising number of users invites hackers …
Collective anomaly detection based on long short-term memory recurrent neural networks
Intrusion detection for computer network systems is becoming one of the most critical tasks
for network administrators today. It has an important role for organizations, governments and …
for network administrators today. It has an important role for organizations, governments and …
Security issues in Internet of Vehicles (IoV): A comprehensive survey
Nowadays, connected vehicles have a major role in enhancing the driving experience.
Connected vehicles in the network share their knowledge with the help of the network …
Connected vehicles in the network share their knowledge with the help of the network …