Gil Einziger

Senior Academic

Volumetric hierarchical heavy hitters

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

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.

Publication language English
Pages 381-392
Publication status Published - 07.11.2018

ASJC Scopus subject areas

Modeling and Simulation
Computer Networks and Communications
Access to Document
10.1109/MASCOTS.2018.00045
Other files and links
Link to publication in Scopus