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Improving Accuracy for Intrusion Detection through Layered Approach Using Support Vector Machine with Feature Reduction

Published: 21 March 2016 Publication History

Abstract

Digital information security is the field of information technology which deal with all about identification and protection of information. Whereas, identification of the threat of any Intrusion Detection System (IDS) in the most challenging phase. Threat detection become most promising because rest of the IDS system phase depends on the solely on "what is identified". In this view, a multilayered framework has been discussed which handles the underlying features for the identification of various attack (DoS, R2L, U2R, Probe). The experiments validates the use SVM with genetic approach is efficient.

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Cited By

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  • (2021)Deep Learning Approaches for Intrusion Detection System2021 IEEE International Conference on Technology, Research, and Innovation for Betterment of Society (TRIBES)10.1109/TRIBES52498.2021.9751643(1-6)Online publication date: 17-Dec-2021
  • (2021)Predictive machine learning-based integrated approach for DDoS detection and preventionMultimedia Tools and Applications10.1007/s11042-021-11740-zOnline publication date: 3-Dec-2021
  • (2019)Intrusion detection using dimensionality reduced soft matrixProceedings of the 5th International Conference on Engineering and MIS10.1145/3330431.3330465(1-7)Online publication date: 6-Jun-2019
  • Show More Cited By

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cover image ACM Other conferences
WIR '16: Proceedings of the ACM Symposium on Women in Research 2016
March 2016
179 pages
ISBN:9781450342780
DOI:10.1145/2909067
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 March 2016

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Author Tags

  1. Genetic Algorithm
  2. NSL KDD dataset
  3. Support Vector Machine

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WIR '16
WIR '16: Women in Research 2016
March 21 - 22, 2016
Indore, India

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WIR '16 Paper Acceptance Rate 35 of 117 submissions, 30%;
Overall Acceptance Rate 35 of 117 submissions, 30%

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Cited By

View all
  • (2021)Deep Learning Approaches for Intrusion Detection System2021 IEEE International Conference on Technology, Research, and Innovation for Betterment of Society (TRIBES)10.1109/TRIBES52498.2021.9751643(1-6)Online publication date: 17-Dec-2021
  • (2021)Predictive machine learning-based integrated approach for DDoS detection and preventionMultimedia Tools and Applications10.1007/s11042-021-11740-zOnline publication date: 3-Dec-2021
  • (2019)Intrusion detection using dimensionality reduced soft matrixProceedings of the 5th International Conference on Engineering and MIS10.1145/3330431.3330465(1-7)Online publication date: 6-Jun-2019
  • (2018)Detection Approaches for Categorization of Spam and Legitimate E-MailHandbook of Research on Pattern Engineering System Development for Big Data Analytics10.4018/978-1-5225-3870-7.ch016(274-296)Online publication date: 2018
  • (2018)Genetic Annealing-Based IDS System for Attack DetectionProceedings of International Conference on Recent Advancement on Computer and Communication10.1007/978-981-10-8198-9_64(619-627)Online publication date: 19-Apr-2018
  • (2018)Data Mining Models for Anomaly Detection Using Artificial Immune SystemProceedings of International Conference on Recent Advancement on Computer and Communication10.1007/978-981-10-8198-9_44(425-432)Online publication date: 19-Apr-2018
  • (2018)Remapping Attack Detection and Prevention for Reliable Data Service in MANETProceedings of International Conference on Recent Advancement on Computer and Communication10.1007/978-981-10-8198-9_13(125-134)Online publication date: 19-Apr-2018
  • (2018)Impact of Various Networks Security Attacks on Wireless Sensor Localization Algorithms Based upon WSN Node’s Residual EnergyProceedings of International Conference on Recent Advancement on Computer and Communication10.1007/978-981-10-8198-9_1(1-10)Online publication date: 19-Apr-2018
  • (2017)NAIDS design using ChiMIC-KGS2017 International Symposium on Electronics and Smart Devices (ISESD)10.1109/ISESD.2017.8253362(346-351)Online publication date: Oct-2017
  • (2017)An enhanced J48 classification algorithm for the anomaly intrusion detection systemsCluster Computing10.1007/s10586-017-1109-8Online publication date: 5-Sep-2017

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