Gatling: Automatic Performance Attack Discovery in Large-Scale Distributed Systems

In this article, we propose Gatling, a framework that automatically finds performance attacks caused by insider attackers in large-scale message-passing distributed systems. In performance attacks, malicious nodes deviate from the protocol when sending or creating messages, with the goal of degrading system performance. We identify a representative set of basic malicious message delivery and lying actions and design a greedy search algorithm that finds effective attacks consisting of a subset of these actions. Although lying malicious actions are protocol dependent, requiring the format and meaning of messages, Gatling captures them without needing to modify the target system by using a type-aware compiler. We have implemented and used Gatling on nine systems, a virtual coordinate system, a distributed hash table lookup service and application, two multicast systems and one file sharing application, and three secure systems designed specifically to tolerate insiders, two based on virtual coordinates and one using Outlier Detection, one invariant derived from physical laws, and the last one a Byzantine resilient replication system. We found a total of 48 attacks, with the time needed to find each attack ranging from a few minutes to a few hours.