Towards Inference of DDoS Mitigation Rules
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F22%3A10133463" target="_blank" >RIV/63839172:_____/22:10133463 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9789798" target="_blank" >https://ieeexplore.ieee.org/document/9789798</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NOMS54207.2022.9789798" target="_blank" >10.1109/NOMS54207.2022.9789798</a>
Alternative languages
Result language
angličtina
Original language name
Towards Inference of DDoS Mitigation Rules
Original language description
DDoS attacks still represent a severe threat to network services. While there are more or less workable solutions to defend against these attacks, there is a significant space for further research regarding automation of reactions and subsequent management. In this paper, we focus on one piece of the whole puzzle. We strive to automatically infer filtering rules which are specific to the current DoS attack to decrease the time to mitigation. We employ a machine learning technique to create a model of the traffic mix based on observing network traffic during the attack and normal period. The model is converted into the filtering rules. We evaluate our approach with various setups of hyperparameters. The results of our experiments show that the proposed approach is feasible in terms of the capability of inferring successful filtering rules.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/VI20192022137" target="_blank" >VI20192022137: Adaptive protection against DDoS attacks</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022
ISBN
978-1-66540-601-7
ISSN
2374-9709
e-ISSN
—
Number of pages
5
Pages from-to
1-5
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Budapest, Hungary
Event location
Budapest, Hungary
Event date
Apr 25, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000851572700054