Adversary-Augmented Simulation to evaluate order-fairness on HyperLedger Fabric - Mahe, Erwan; Abdallah, Rouwaida; Tucci-Piergiovanni, Sara; Piriou, Pierre-Yves (Anais do Latin-American Symposium on Dependable Computing (LADC); 2024: Anais do XIII Latin-American Symposium on Dependable Computing, 2024)
This paper presents an adversary model specifically tailored to the simulation of attacks on distributed systems which combine several distributed protocols, with the aim to assess the security of blockchain networks. Our model classifies and constrains the use of adversarial actions based on the target protocols assumptions defined by both failure and communication models as well as by the tolerance thresholds of Byzantine Fault Tolerant protocols. The objective is to study the side effects of adversarial attacks (which combine these allowed actions) on properties of the distributed system beyond the intended effect related to the goal of the adversary. A significant aspect of our research involves integrating this adversary model into the Multi-Agent eXperimenter (MAX) framework. This integration enables fine-grained simulations of adversarial attacks on blockchain networks.In this paper, we particularly study fairness properties on a Hyperledger Fabric (HF) blockchain network with the Byzantine Fault Tolerant Tendermint consensus protocol being selected as the underlying consensus protocol. We define novel attacks that combine adversarial actions on the different services provided by the HF blockchain network, with the aim of violating a specific client-fairness property. Simulations confirm the adversary’s ability to violate this property and allow us to evaluate the impact of these attacks on other order-fairness properties, which correlate the order of transaction reception by individual nodes and the subsequent order of transactions within the blockchain.