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Comparative analysis of intrusion detection systems and machine learning-based model analysis through decision tree
Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions
With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …
between different communicating devices. The data should be communicated securely …
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 …
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 …
An intrusion detection system for connected vehicles in smart cities
In the very near future, transportation will go through a transitional period that will shape the
industry beyond recognition. Smart vehicles have played a significant role in the …
industry beyond recognition. Smart vehicles have played a significant role in the …
HAST-IDS: Learning hierarchical spatial-temporal features using deep neural networks to improve intrusion detection
The development of an anomaly-based intrusion detection system (IDS) is a primary
research direction in the field of intrusion detection. An IDS learns normal and anomalous …
research direction in the field of intrusion detection. An IDS learns normal and anomalous …
A mechanism for detecting the intruder in the network through a stacking dilated CNN model
Rapid advancements in the technology and telecommunication areas have led to a massive
expansion of network density and information. As a consequence, numerous intruder …
expansion of network density and information. As a consequence, numerous intruder …
Survey on anomaly detection using data mining techniques
In the present world huge amounts of data are stored and transferred from one location to
another. The data when transferred or stored is primed exposed to attack. Although various …
another. The data when transferred or stored is primed exposed to attack. Although various …
Cyber threat detection using machine learning techniques: A performance evaluation perspective
The present-day world has become all dependent on cyberspace for every aspect of daily
living. The use of cyberspace is rising with each passing day. The world is spending more …
living. The use of cyberspace is rising with each passing day. The world is spending more …
Hybrid decision tree and naïve Bayes classifiers for multi-class classification tasks
In this paper, we introduce two independent hybrid mining algorithms to improve the
classification accuracy rates of decision tree (DT) and naïve Bayes (NB) classifiers for the …
classification accuracy rates of decision tree (DT) and naïve Bayes (NB) classifiers for the …