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Intrusion Detection in NEAR System by Anti-denoising Traffic Data Series using Discrete Wavelet TransformVANCEA, F.   |
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Author keywords
discrete wavelet transform, intrusion detection, self-similarity, signal denoising, time-frequency analysis
References keywords
traffic(9), wavelet(8), processing(7), network(7), detection(7), signal(6), analysis(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2014-11-30
Volume 14, Issue 4, Year 2014, On page(s): 43 - 48
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.04007
Web of Science Accession Number: 000348772500007
SCOPUS ID: 84921631227
Abstract
The paper presents two methods for detecting anomalies in data series derived from network traffic. Intrusion detection systems based on network traffic analysis are able to respond to incidents never seen before by detecting anomalies in data series extracted from the traffic. Some anomalies manifest themselves as pulses of various sizes and shapes, superimposed on series corresponding to normal traffic. In order to detect those impulses we propose two methods based on discrete wavelet transformation. Their effectiveness expressed in relative thresholds on pulse amplitude for no false negatives and no false positives is then evaluated against pulse duration and Hurst characteristic of original series. Different base functions are also evaluated for efficiency in the context of the proposed methods. |
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[1] Performance of discrete wavelet transform‐based method in the detection of influenza outbreaks in Iran: An ecological study, Minaeian, Sara, Alimohamadi, Yousef, Eshrati, Babak, Esmaeilzadeh, Firooz, Health Science Reports, ISSN 2398-8835, Issue 5, Volume 6, 2023.
Digital Object Identifier: 10.1002/hsr2.1245 [CrossRef]
[2] A new approach for internet traffic classification: GA-WK-ELM, Ertam, Fatih, Avcı, Engin, Measurement, ISSN 0263-2241, Issue , 2017.
Digital Object Identifier: 10.1016/j.measurement.2016.10.001 [CrossRef]
[3] RULE GENERATION BASED ON MODIFIED CUTTLEFISH ALGORITHM FOR INTRUSION DETECTION SYSTEM, EESA, Adel Sabry, SADIQ, Sheren, HASSAN, Masoud, ORMAN, Zeynep, Uludağ University Journal of The Faculty of Engineering, ISSN 2148-4147, 2021.
Digital Object Identifier: 10.17482/uumfd.747078 [CrossRef]
[4] Some results on intrusion and anomaly detection using signal processing and NEAR system, Vancea, Florin, Vancea, Codruta, 2015 38th International Conference on Telecommunications and Signal Processing (TSP), ISBN 978-1-4799-8498-5, 2015.
Digital Object Identifier: 10.1109/TSP.2015.7296234 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
