# Denial-of-Service Attacks on Permissioned Blockchains: A Practical Study
## 3 Related Work  
DoS attacks pose a critical threat to the security and functionality of HLF. Prior research has extensively investigated vulnerabilities across various elements of HLF, including ordering services, consensus mechanisms, endorsement processes, and application-level components. While these studies offer valuable insights, they vary significantly in scope, methodology, and targeted subsystems. To highlight both the breadth and fragmentation of existing DoS-related research on HLF, Table 1 organizes prior studies by subsystem and method. While these studies offer valuable insights, their findings often lack integration, and few directly inform real-world attack design. By critically synthesizing their methodologies, we identify the gaps that shaped our experimental setup.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline Study & Methodology & Main Findings \\ \hline \multicolumn{3}{c}{Ordering Service Vulnerabilities} \\ \hline [PERSON] et al. (2019) [36] and [PERSON] (2021) [37] & Systematic modeling of attack scenarios on HotStuff. & Identified vulnerabilities due to block withholding and batch size manipulation in the ordering service. \\ [PERSON] et al. (2024) [38] & \begin{tabular}{c} Artificial analysis of Raft-based ordering. \\ Simulated transaction flooding on Ethereum and Fabric. \\ \end{tabular} & Highlighted DoS risks via Raft leader election manipulation through timeout abuse. \\ \hline \multicolumn{3}{c}{Consensus Protocol Vulnerabilities} \\ \hline [PERSON] et al. (2024) [39] & \begin{tabular}{c} Simulated low-bandwidth DoS attacks on HotStuff. \\ Benchmarked PBFT, Raft, and PoET under DDoS in Sawtooth. \\ Flood-based attack simulations on Raft in HLF and Ethereum. \\ Evaluated SGX-based EGES protocol on Ethereum. \\ \end{tabular} & Showed that attacks as low as 30 Mbps can halt HotStuff. \\ [PERSON] et al. (2022) [40] & \begin{tabular}{c} Bounded PBFT, Raft, and PoET under DDoS in Sawtooth. \\ Flood-based attack simulations on Raft in HLF and Ethereum. \\ Evaluated SGX-based EGES protocol on Ethereum. \\ \end{tabular} & Found Raft suffered the most degradation (latency, packet loss); proposed adaptive switching strategy. \\ [PERSON] et al. (2023) [41] & \begin{tabular}{c} Confirmed Raft’s vulnerability; HLF showed CPU overload, latency rise, and packet loss. \\ EGES showed DoS resilience and scalability on Ethereum. \\ \end{tabular} & \begin{tabular}{c} Enhanced Layer Vulnerabilities \\ \end{tabular} \\ [PERSON] et al. (2022) [42] & \
\begin{tabular}{c} Simulated targeted DoS attacks by sending a high rate of transactions to selected endorsers. \\ Simulated SHA-256-based dynamic endorser selection. \\ \end{tabular} &
\begin{tabular}{c} Found that attacking 2 endorsers caused a 20\% throughput drop and a 75\% latency increase; proposed VRF-based randomized endorsement. \\ Mitigated risk from static endorser configurations and reduced attack success rate by nearly 50\%. \\ Showed that colluding peers can selectively refuse endorsements; proposed diversified policies without empirical testing. \\ Sybil nodes increased endorsement delays and MVCC conflicts and disrupted the transaction flow. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of related studies.