Versatile yet Efficient Network Traffic Analysis: Offloading Network Foundation Model to SmartNIC
Chungang Lin, Xuying Meng, Tianyu Zuo, Weiyao Zhang, Meng Shen, Ruijie Zhao, Guanming Che, Ruiqi Meng, Ziyue Huang, Haitong Luo, Zhiwei Xu, Yujun Zhang

TL;DR
Nepco is a novel system that offloads network foundation models to SmartNICs, enabling versatile and efficient traffic analysis by focusing on localized byte sequences and employing a pattern-aware convolutional architecture.
Contribution
The paper introduces Nepco, a hardware-friendly, localized byte-sequence modeling approach that maintains versatility and significantly reduces latency in network traffic analysis.
Findings
Nepco achieves macro F1 scores comparable to 8 state-of-the-art models.
Nepco reduces end-to-end latency by 328 times, reaching millisecond scale.
Nepco demonstrates effective analysis on Nvidia BlueField-3 SmartNIC.
Abstract
Pervasive encryption makes large-scale labeling infeasible for traffic analysis, while security operations demand edge analysis to avert service degradation and further vulnerabilities. These pressures have produced two disjoint research lines: 1) versatile analysis, via network foundation models for low label dependency, and 2) efficient analysis, via hardware offloading for low analysis latency. However, versatility and efficiency have appeared fundamentally incompatible to co-achieve, with prior work consistently sacrificing one for the other, yet we show that this incompatibility is a consequence of polarized design choices across the three components of traffic analysis systems, i.e., traffic processing, model architecture, and analysis execution. In response, we present Nepco, a versatile yet efficient network traffic analysis system that offloads network foundation models to…
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