Intrusion detection by machine learning: A review
CF Tsai, YF Hsu, CY Lin, WY Lin - expert systems with applications, 2009 - Elsevier
The popularity of using Internet contains some risks of network attacks. Intrusion detection is
one major research problem in network security, whose aim is to identify unusual access or …
one major research problem in network security, whose aim is to identify unusual access or …
The use of computational intelligence in intrusion detection systems: A review
SX Wu, W Banzhaf - Applied soft computing, 2010 - Elsevier
Intrusion detection based upon computational intelligence is currently attracting
considerable interest from the research community. Characteristics of computational …
considerable interest from the research community. Characteristics of computational …
An efficient intrusion detection system based on support vector machines and gradually feature removal method
Y Li, J **a, S Zhang, J Yan, X Ai, K Dai - Expert systems with applications, 2012 - Elsevier
The efficiency of the intrusion detection is mainly depended on the dimension of data
features. By using the gradually feature removal method, 19 critical features are chosen to …
features. By using the gradually feature removal method, 19 critical features are chosen to …
A survey on the application of genetic programming to classification
Classification is one of the most researched questions in machine learning and data mining.
A wide range of real problems have been stated as classification problems, for example …
A wide range of real problems have been stated as classification problems, for example …
Feature deduction and ensemble design of intrusion detection systems
S Chebrolu, A Abraham, JP Thomas - Computers & security, 2005 - Elsevier
Current intrusion detection systems (IDS) examine all data features to detect intrusion or
misuse patterns. Some of the features may be redundant or contribute little (if anything) to …
misuse patterns. Some of the features may be redundant or contribute little (if anything) to …
Intrusion Detection System (IDS): Anomaly detection using outlier detection approach
Abstract An Intrusion Detection System (IDS) is a software application or device that
monitors the system or activities of network for policy violations or malicious activities and …
monitors the system or activities of network for policy violations or malicious activities and …
Modeling intrusion detection system using hybrid intelligent systems
The process of monitoring the events occurring in a computer system or network and
analyzing them for sign of intrusions is known as intrusion detection system (IDS). This …
analyzing them for sign of intrusions is known as intrusion detection system (IDS). This …
Applying long short-term memory recurrent neural networks to intrusion detection
RC Staudemeyer - South African Computer Journal, 2015 - journals.co.za
We claim that modelling network traffic as a time series with a supervised learning approach,
using known genuine and malicious behaviour, improves intrusion detection. To …
using known genuine and malicious behaviour, improves intrusion detection. To …
A hybrid network intrusion detection system using simplified swarm optimization (SSO)
The network intrusion detection techniques are important to prevent our systems and
networks from malicious behaviors. However, traditional network intrusion prevention such …
networks from malicious behaviors. However, traditional network intrusion prevention such …
Discriminative multinomial naive bayes for network intrusion detection
This paper applies discriminative multinomial Naïve Bayes with various filtering analysis in
order to build a network intrusion detection system. For our experimental analysis, we used …
order to build a network intrusion detection system. For our experimental analysis, we used …