Volumetric hierarchical heavy hitters

Ran Ben Basat, Gil Einziger, Roy Friedman, Marcelo Caggiani Luizelli, Erez Waisbard

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Hierarchical heavy hitters (HHH) identification is useful for various network utilities such as anomaly detection, DDoS mitigation, and traffic analysis. However, the increasing support for jumbo frames enables attackers to overload the system with fewer packets, avoiding detection by packet counting techniques. This paper suggests an efficient algorithm for detecting HHH based on their traffic volume that asymptotically improves the runtime of previous works. We implement our algorithm in Open vSwitch (OVS) and incur a 4−6% overhead compared to a 42% throughput reduction experienced by the state-of-the-art.

Original languageEnglish
Title of host publicationProceedings - 26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages381-392
Number of pages12
ISBN (Electronic)9781538668863
DOIs
StatePublished - 7 Nov 2018
Externally publishedYes
Event26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018 - Milwaukee, United States
Duration: 25 Sep 201828 Sep 2018

Publication series

NameProceedings - 26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018
Volume2018-January

Conference

Conference26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018
Country/TerritoryUnited States
CityMilwaukee
Period25/09/1828/09/18

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