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
Modified marine predators algorithm for feature selection: case study metabolomics
TL;DR: An FS method based on a new modified version of the marine predators algorithm (MPA) has significant performance, and it outperforms the compared methods in terms of classification measures.
Journal ArticleDOI
A GBDT-Paralleled Quadratic Ensemble Learning for Intrusion Detection System
TL;DR: A Gradient Boosting Decision Tree (GBDT)-paralleled quadratic ensemble learning method for intrusion detection system that achieves better accuracy, recall, precision and F1 score than the state-of-the-art methods.
Journal ArticleDOI
Effective feature selection technique in an integrated environment using enhanced principal component analysis
D. Hemavathi,H. Srimathi +1 more
TL;DR: This research focuses the feature selection by the Enhanced Principal Component Analysis (EPCA) algorithm, which gives better results in supervised, unsupervised environment and it has been tested various numerical and text data in various learning environment.
Journal ArticleDOI
A new intrusion detection system based on Moth-Flame Optimizer algorithm
Journal ArticleDOI
A Statistical Approach for Detection of Denial of Service Attacks in Computer Networks
TL;DR: The proposed CSR and FDM based statistical approach for detecting DoS attacks yields significant results compared to the existing feature selection and extraction techniques and state-of-the-art attack detection systems.
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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