Volumetric Hierarchical Heavy Hitters
Ran Ben Basat, Gil Einziger, Roy Friedman, Marcelo Caggiani Luizelli, Erez Waisbard · 2018
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.