Journal ArticleDOI
Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model
TLDR
A new hybrid model can be used to estimate the intrusion scope threshold degree based on the network transaction data’s optimal features that were made available for training and revealed that the hybrid approach had a significant effect on the minimisation of the computational and time complexity involved when determining the feature association impact scale.About:
This article is published in Journal of Computational Science.The article was published on 2017-03-22. It has received 484 citations till now. The article focuses on the topics: Anomaly-based intrusion detection system & Intrusion detection system.read more
Citations
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Journal ArticleDOI
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier
TL;DR: Wang et al. as discussed by the authors proposed a new intrusion detection framework based on the feature selection and ensemble learning techniques, and this framework is able to exhibit better performance than other related and state of the art approaches under several metrics.
Journal ArticleDOI
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
TL;DR: An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode and demonstrates that ISSA outperforms all baseline algorithms in terms of fitness values, accuracy, convergence curves, and feature reduction in most of the used datasets.
Journal ArticleDOI
A feature selection algorithm for intrusion detection system based on Pigeon Inspired Optimizer
TL;DR: A new method to binarize a continuous pigeon inspired optimizer is proposed and compared to the traditional way for binarizing continuous swarm intelligent algorithms.
Journal ArticleDOI
Passban IDS: An Intelligent Anomaly-Based Intrusion Detection System for IoT Edge Devices
TL;DR: Passban is presented, an intelligent intrusion detection system (IDS) able to protect the IoT devices that are directly connected to it that can be deployed directly on very cheap IoT gateways, taking full advantage of the edge computing paradigm to detect cyber threats as close as possible to the corresponding data sources.
Journal ArticleDOI
Dimensionality reduction with IG-PCA and ensemble classifier for network intrusion detection
TL;DR: Experimental results show that the proposed hybrid dimensionality reduction method with the ensemble of the base learners contributes more critical features and significantly outperforms individual approaches, achieving high accuracy and low false alarm rates.
References
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Proceedings ArticleDOI
Multi-column deep neural networks for image classification
TL;DR: In this paper, a biologically plausible, wide and deep artificial neural network architectures was proposed to match human performance on tasks such as the recognition of handwritten digits or traffic signs, achieving near-human performance.
Proceedings Article
Bro: a system for detecting network intruders in real-time
TL;DR: Bro as mentioned in this paper is a stand-alone system for detecting network intruders in real-time by passively monitoring a network link over which the intruder's traffic transits, which emphasizes high-speed (FDDI-rate) monitoring, realtime notification, clear separation between mechanism and policy and extensibility.
Journal ArticleDOI
Bro: a system for detecting network intruders in real-time
Vern Paxson,Vern Paxson +1 more
TL;DR: An overview of the Bro system's design, which emphasizes high-speed (FDDI-rate) monitoring, real-time notification, clear separation between mechanism and policy, and extensibility, is given.
Journal ArticleDOI
Testing Intrusion detection systems: a critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by Lincoln Laboratory
TL;DR: The purpose of this article is to attempt to identify the shortcomings of the Lincoln Lab effort in the hope that future efforts of this kind will be placed on a sounder footing.
Proceedings ArticleDOI
An Intrusion-Detection Model
TL;DR: A model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described, based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage.
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