LoRDMA: A New Low-Rate DoS Attack in RDMA Networks
Shicheng Wang, Menghao Zhang, Yuying Du, Ziteng Chen, Zhiliang Wang, Mingwei Xu, Renjie Xie, Jiahai Yang
摘要
—RDMA is being widely used from private data center applications to multi-tenant clouds, which makes RDMA security gain tremendous attention. However, existing RDMA security studies mainly focus on the security of RDMA systems, and the security of the coupled traffic control mechanisms (represented by PFC and DCQCN) in RDMA networks is largely overlooked. In this paper, through extensive experiments and analysis, we demonstrate that concurrent short-duration bursts can cause drastic performance loss on flows across multiple hops via the interaction between PFC and DCQCN. And we also summarize the vulnerabilities between the performance loss and the burst peak rate, as well as the duration. Based on these vulnerabilities, we propose the LoRDMA attack, a low-rate DoS attack against RDMA traffic control mechanisms. By monitoring RTT as the feedback signal, LoRDMA can adaptively 1) coordinate the bots to different target switch ports to cover more victim flows efficiently; 2) schedule the burst parameters to cause significant performance loss efficiently. We conduct and evaluate the LoRDMA attack at both ns-3 simulations and a cloud RDMA cluster. The results show that compared to existing attacks, the LoRDMA attack achieves higher victim flow coverage and performance loss with much lower attack traffic and detectability. And the communication performance of typical distributed machine learning training applications ( NCCL Tests ) in the cloud RDMA cluster can be degraded from 18.23% to 56.12% under the LoRDMA attack.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- Hawkeye: Diagnosing RDMA Network Performance Anomalies with PFC ProvenanceShicheng Wang, Menghao Zhang, Xiao Li, Qiyang Peng 等SIGCOMM 2025 · 被引用 7 次
- Janus: Enabling Expressive and Efficient ACLs in High-speed RDMA CloudsZiteng Chen, Menghao Zhang, Jiahao Cao, Xuzheng Chen 等NDSS 2026
它引用的顶会 Paper29
- A Unified Architecture for Accelerating Distributed DNN Training in Heterogeneous GPU/CPU ClustersYimin Jiang, Yibo Zhu, Chang Lan, Bairen Yi 等OSDI 2020 · 被引用 390 次
- ATP: In-network Aggregation for Multi-tenant LearningChonLam Lao, Yanfang Le, Kshiteej Mahajan, Yixi Chen 等NSDI 2021 · 被引用 359 次
- Swift: Delay is Simple and Effective for Congestion Control in the DatacenterGautam Kumar, Nandita Dukkipati, Keon Jang, Hassan M. G. Wassel 等SIGCOMM 2020 · 被引用 333 次
- When Cloud Storage Meets RDMAYixiao Gao, Qiang Li, Lingbo Tang, Yongqing Xi 等NSDI 2021 · 被引用 228 次
- SP-PIFO: Approximating Push-In First-Out Behaviors using Strict-Priority QueuesAlbert Gran Alcoz, Alexander Dietmüller, Laurent VanbeverNSDI 2020 · 被引用 140 次
相关 Paper
- PACC: Proactive and Accurate Congestion Feedback for RDMA Congestion ControlXiaolong Zhong, Jiao Zhang, Yali Zhang, Zixuan Guan 等INFOCOM 2022 · 被引用 36 次
- ReDMArk: Bypassing RDMA Security MechanismsBenjamin Rothenberger, Konstantin Taranov, Adrian Perrig, Torsten HoeflerUSENIX Security 2021 · 被引用 56 次
- sRDMA - Efficient NIC-based Authentication and Encryption for Remote Direct Memory AccessKonstantin Taranov, Benjamin Rothenberger, Adrian Perrig, Torsten HoeflerUSENIX ATC 2020 · 被引用 59 次
- Bedrock: Programmable Network Support for Secure RDMA SystemsJiarong Xing, Kuo-Feng Hsu, Yiming Qiu, Ziyang Yang 等USENIX Security 2022
- Quantifying Rowhammer Vulnerability for DRAM SecurityYichen Jiang, Huifeng Zhu, Dean Sullivan, Xiaolong Guo 等DAC 2021 · 被引用 20 次
