Literature Database Entry
erlacher2017high
Felix Erlacher and Falko Dressler, "High Performance Intrusion Detection Using HTTP-based Payload Aggregation," Proceedings of 42nd IEEE Conference on Local Computer Networks (LCN 2017), Singapore, Singapore, October 2017, pp. 418–425.
Abstract
Signature-based Network Intrusion Detection Systems (NIDS) are an integral part of modern network security solutions. They help to detect and prevent network attacks and intrusions. However, they show critical performance problems in today’s high speed networks. Filters have been proposed to reduce the amount of traffic to be analyzed by a NIDS, yet, such filters need to be very carefully designed in order not to miss relevant data. We address this problem by proposing a novel concept for filtering taking into account the pipelining architecture of modern web traffic. Our concept, which we named HTTP-based Payload Aggregation (HPA), is able to retain the first N bytes of the basic Protocol Data Unit (PDU) of an application layer protocol and discard the rest, arguing that the retained payload portion contains almost all relevant data for intrusion detection. We demonstrate the feasibility of our approach focusing on HTTP traffic as the most prominent protocol in many Internet applications. The idea is, thus, to capture the first N bytes of every pipelined session and forward this data to a NIDS. In our evaluation, we show that for the used traces we still detect more than 97% of the events with only 2.5% of the network traffic to be analyzed. We achieve an increase in packet throughput of up to 44 in our experiments.
Quick access
Original Version (at publishers web site)
Authors' Version (PDF on this web site)
BibTeX
Contact
BibTeX reference
@inproceedings{erlacher2017high,
author = {Erlacher, Felix and Dressler, Falko},
doi = {10.1109/LCN.2017.18},
title = {{High Performance Intrusion Detection Using HTTP-based Payload Aggregation}},
pages = {418--425},
publisher = {IEEE},
address = {Singapore, Singapore},
booktitle = {42nd IEEE Conference on Local Computer Networks (LCN 2017)},
month = {10},
year = {2017},
}
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.