一句话:提出面向有状态可编程数据平面的概率剖析方法,以支持对抗性测试。
可编程交换机上的数据平面系统正变得越来越复杂,其处理逻辑远超传统的下一跳转发,且通常带有状态。现有的网络程序剖析器主要面向无状态转发程序,无法有效应对有状态数据平面的剖析需求。为此,本文提出面向有状态数据平面的概率剖析(probabilistic profiling)方法,旨在刻画此类程序的运行时行为,并服务于对抗性测试。摘要指出了传统剖析器在有状态数据平面场景下的局限,并给出了概率化剖析这一方向,但未详述具体实现与实验数据。
Recently, there is a flurry of projects that develop data plane systems in programmable switches, and these systems perform far more sophisticated processing than simply deciding a packet's next hop (i.e., traditional forwarding). This presents challenges to existing network program profilers, which are developed primarily to handle stateless forwarding programs.
DOI 原文 ·
@inproceedings{paperbot6111,
title = {Probabilistic profiling of stateful data planes for adversarial testing},
author = {Qiao Kang and Jiarong Xing and Yiming Qiu and Ang Chen},
booktitle = {ASPLOS},
year = {2021},
doi = {10.1145/3445814.3446764}
}