Detecting App-DDoS Attacks Based on Marking Access and d-SVDD

DOI

10.2991/isccca.2013.183How to use a DOI?

Keywords

App-DDoS attack, Marking access, d-SVDD, Anomaly detection

Abstract

In order to enhance the extensibility of current attack feature extracted and detection means for App-DDoS(Application Layer Distributed Denial of Service, App-DDoS)attacks, a novel feature extracted method based on marking access and a new detection algorithm named d-SVDD are proposed. After expressing kinds of App-DDoS attacks as characteristic vectors by access marked strategy and feature extracted strategy, d-SVDD algorithm is used for secondary classification and detection of pre-set area around decision boundary based on SVDD. It is proved by experiments that the proposed feature extracted and detection means can realize effective detection for kinds of App-DDoS attacks, both have satisfying time, space and extensibility performance.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jin-ling LI
AU  - Bin-qiang Wang
PY  - 2013/02
DA  - 2013/02
TI  - Detecting App-DDoS Attacks Based on Marking Access and d-SVDD
BT  - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)
PB  - Atlantis Press
SP  - 728
EP  - 732
SN  - 1951-6851
UR  - https://doi.org/10.2991/isccca.2013.183
DO  - 10.2991/isccca.2013.183
ID  - LI2013/02
ER  -