Literature Database Entry

doroud2023l-ids

Hossein Doroud, Omar Alkhateeb, Elnaz Alizadeh Jarchlo and Falko Dressler, "L-IDS: A Lifelong Learning Approach for Intrusion Detection," Proceedings of IEEE International Wireless Communications & Mobile Computing Conference (IWCMC 2023), Marrakesh, Morocco, June 2023, pp. 482–487.

Abstract

Intrusion detection systems (IDS) represent a class of defensive security tools with the purpose of protecting the network from intruders in the network administrators arsenal. Despite the high precision of traditional signature-based IDS, its effectiveness is still under question due to the growth of a number of encrypted attacks and the volume of network traffic. This is considered as one of the main motivations for researchers to develop anomaly-based IDS, which usually suffer from higher false positive rate. In this paper, we propose and implement a lifelong- learning anomaly detection IDS (L-IDS) with the capability of the network environment’s adaption to limit the false positive rate of anomaly detector in the range of signateure-based IDS. We consider Snort as a baseline and UNSW-NB15 as the ground truth in the evaluation of our proposal. We demonstrate how L-IDS achieves a higher level of precision in comparison with the existing signature-based IDS.

Quick access

Original Version DOI (at publishers web site)
Authors' Version PDF (PDF on this web site)
BibTeX BibTeX

Contact

Hossein Doroud
Omar Alkhateeb
Elnaz Alizadeh Jarchlo
Falko Dressler

BibTeX reference

@inproceedings{doroud2023l-ids,
    author = {Doroud, Hossein and Alkhateeb, Omar and Alizadeh Jarchlo, Elnaz and Dressler, Falko},
    doi = {10.1109/IWCMC58020.2023.10182443},
    title = {{L-IDS: A Lifelong Learning Approach for Intrusion Detection}},
    pages = {482--487},
    publisher = {IEEE},
    issn = {2376-6506},
    address = {Marrakesh, Morocco},
    booktitle = {IEEE International Wireless Communications \& Mobile Computing Conference (IWCMC 2023)},
    month = {6},
    year = {2023},
   }
   
   

Copyright notice

Links to final or draft versions of papers are presented here to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or distributed for commercial purposes without the explicit permission of the copyright holder.

The following applies to all papers listed above that have IEEE copyrights: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

The following applies to all papers listed above that are in submission to IEEE conference/workshop proceedings or journals: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

The following applies to all papers listed above that have ACM copyrights: ACM COPYRIGHT NOTICE. Permission to make digital or hard copies of part or all 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, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or permissions@acm.org.

The following applies to all SpringerLink papers listed above that have Springer Science+Business Media copyrights: The original publication is available at www.springerlink.com.

This page was automatically generated using BibDB and bib2web.