CC-fuzz: genetic algorithm-based fuzzing for stress testing congestion control algorithms
CC-fuzz: genetic algorithm-based fuzzing for stress testing congestion control algorithms
复制标题
CC-fuzz：基于遗传算法的模糊测试，用于压力测试拥塞控制算法
DOI：
10.1145/3563766.3564088
复制
发表时间：
2022
期刊：
影响因子：
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通讯作者：
Seshan, Srinivasan
中科院分区：
文献类型：
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作者：
Ray, Devdeep;Seshan, Srinivasan
最近的拥塞控制研究集中在为特定应用的特殊需求而设计的专门构建的算法上。由于CCA与其他现有CCA和不同网络环境的交互方式复杂，在部署CCA之前进行的有限测试通常会导致不可预见且难以调试的性能问题。我们提出了CC-Fuzz，这是一个自动化框架，它使用遗传搜索算法来生成敌对网络轨迹和流量模式，用于压力测试CCA。初步结果包括CC-Fuzz自动发现BBR中导致其永久停止的错误，以及自动发现众所周知的低速率TCP攻击等。
Recent congestion control research has focused on purpose-built algorithms designed for the special needs of specific applications. Often, limited testing before deploying a CCA results in unforeseen and hard-to-debug performance issues due to the complex ways a CCA interacts with other existing CCAs and diverse network environments. We present CC-Fuzz, an automated framework that uses genetic search algorithms to generate adversarial network traces and traffic patterns for stress-testing CCAs. Initial results include CC-Fuzz automatically finding a bug in BBR that causes it to stall permanently, and automatically discovering the well-known low-rate TCP attack, among other things.
DOI：
10.1145/3232755.3232769
发表时间：
2018-07
期刊：
Proceedings of the Applied Networking Research Workshop
影响因子：
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作者：
Samuel Jero;Md. Endadul Hoque;D. Choffnes;A. Mislove;C. Nita-Rotaru
通讯作者：
Samuel Jero;Md. Endadul Hoque;D. Choffnes;A. Mislove;C. Nita-Rotaru