An enhanced anomaly detection in web traffic using a stack of classifier ensemble
A Web attack protection system is extremely essential in today's information age. Classifier
ensembles have been considered for anomaly-based intrusion detection in Web traffic …
ensembles have been considered for anomaly-based intrusion detection in Web traffic …
A GAN and Feature Selection‐Based Oversampling Technique for Intrusion Detection
In recent years, there have been numerous cyber security issues that have caused
considerable damage to the society. The development of efficient and reliable Intrusion …
considerable damage to the society. The development of efficient and reliable Intrusion …
Towards effective network intrusion detection: from concept to creation on Azure cloud
Network Intrusion Detection is one of the most researched topics in the field of computer
security. Hacktivists use sophisticated tools to launch numerous attacks that hamper the …
security. Hacktivists use sophisticated tools to launch numerous attacks that hamper the …
Hybridizing genetic algorithm and grey wolf optimizer to advance an intelligent and lightweight intrusion detection system for IoT wireless networks
Open wireless sensor networks (WSNs) in Internet of things (IoT) has led to many zero-day
security attacks. Since intrusion detection is a key security solution, this paper presents a …
security attacks. Since intrusion detection is a key security solution, this paper presents a …
A comprehensive intrusion detection framework using boosting algorithms
Abstract Intrusion Detection Systems are one of the most effective technologies that protect
systems against cyber-attacks. In this study, a new Comprehensive Cyber Security Intrusion …
systems against cyber-attacks. In this study, a new Comprehensive Cyber Security Intrusion …
A data-driven network intrusion detection system using feature selection and deep learning
L Zhang, K Liu, X Xie, W Bai, B Wu, P Dong - Journal of Information Security …, 2023 - Elsevier
Network intrusion detection system (NIDS) is an important line of defense for network
security as network attacks become more frequent. In this paper, we propose a data-driven …
security as network attacks become more frequent. In this paper, we propose a data-driven …
A network intrusion detection system based on convolutional neural network
H Wang, Z Cao, B Hong - Journal of Intelligent & Fuzzy …, 2020 - content.iospress.com
Intrusion detection systems (IDSs) play an important point in resisting hacker intrusion. With
the rapid development of the network technology, network security has received more and …
the rapid development of the network technology, network security has received more and …
A steering-matrix-based multiobjective evolutionary algorithm for high-dimensional feature selection
In recent years, multiobjective evolutionary algorithms (MOEAs) have been demonstrated to
show promising performance in feature selection (FS) tasks. However, designing an MOEA …
show promising performance in feature selection (FS) tasks. However, designing an MOEA …
An efficient intrusion detection technique based on support vector machine and improved binary gravitational search algorithm
MR Gauthama Raman, N Somu, S Jagarapu… - Artificial Intelligence …, 2020 - Springer
Abstract 'Curse of Dimensionality'and the trade-off between high detection rate and less
false alarm rate make the design of an efficient and robust Intrusion Detection System, an …
false alarm rate make the design of an efficient and robust Intrusion Detection System, an …
A multi-objective immune algorithm for intrusion feature selection
Feature selection plays a crucial role in classification problems, which tries to remove
redundant or irrelevant features by mapping high-dimensional data to low-dimensional …
redundant or irrelevant features by mapping high-dimensional data to low-dimensional …