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 …
Network anomaly detection: methods, systems and tools
MH Bhuyan, DK Bhattacharyya… - … surveys & tutorials, 2013 - ieeexplore.ieee.org
Network anomaly detection is an important and dynamic research area. Many network
intrusion detection methods and systems (NIDS) have been proposed in the literature. In this …
intrusion detection methods and systems (NIDS) have been proposed in the literature. In this …
IoT intrusion detection using machine learning with a novel high performing feature selection method
The Internet of Things (IoT) ecosystem has experienced significant growth in data traffic and
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …
Toward a lightweight intrusion detection system for the internet of things
Integration of the Internet into the entities of the different domains of human society (such as
smart homes, health care, smart grids, manufacturing processes, product supply chains, and …
smart homes, health care, smart grids, manufacturing processes, product supply chains, and …
From intrusion detection to attacker attribution: A comprehensive survey of unsupervised methods
Over the last five years there has been an increase in the frequency and diversity of network
attacks. This holds true, as more and more organizations admit compromises on a daily …
attacks. This holds true, as more and more organizations admit compromises on a daily …
A survey on big data for network traffic monitoring and analysis
Network Traffic Monitoring and Analysis (NTMA) represents a key component for network
management, especially to guarantee the correct operation of large-scale networks such as …
management, especially to guarantee the correct operation of large-scale networks such as …
Mutual information-based feature selection for intrusion detection systems
As the network-based technologies become omnipresent, threat detection and prevention
for these systems become increasingly important. One of the effective ways to achieve …
for these systems become increasingly important. One of the effective ways to achieve …
An efficient intrusion detection system based on support vector machines and gradually feature removal method
Y Li, J Xia, 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 …
Feature selection and intrusion classification in NSL-KDD cup 99 dataset employing SVMs
Intrusion is the violation of information security policy by malicious activities. Intrusion
detection (ID) is a series of actions for detecting and recognising suspicious actions that …
detection (ID) is a series of actions for detecting and recognising suspicious actions that …
A hybrid method consisting of GA and SVM for intrusion detection system
In this paper, a hybrid method of support vector machine and genetic algorithm (GA) is
proposed and its implementation in intrusion detection problem is explained. The proposed …
proposed and its implementation in intrusion detection problem is explained. The proposed …