Liu Guofang, Fu Chunlong, Yang Xiaofan, Yang Luxing, Feng Yanhua, Qin Yang
Department of Computer Science, Sichuan University Jinjiang College, MeiShan, Sichuan 620860, China.
School of Big Data and Software Engineering, Chongqing University, Chongqing 400044, China.
PLoS One. 2025 May 6;20(5):e0319916. doi: 10.1371/journal.pone.0319916. eCollection 2025.
The lag of antivirus (AV) software development relative to malware development makes it necessary to constantly release AV patches. In practice, an AV patch can be deployed on an organization's intranet only when it passes compatibility test. In this context, a subset of hosts may be assigned to perform the test. The function of the fraction of the assigned hosts with respect to time is referred to as an AV patch testing (AVPT) policy, and the problem of finding a satisfactory AVPT policy in terms of the cost benefit is referred to as the AVPT problem. This paper addresses the AVPT problem through optimal control modeling. A new mathematical model of characterizing the evolution of the intranet's expected state is introduced by incorporating the effect of AV patch testing. On this basis, the AVPT problem is modeled as an optimal control problem (the AVPT model). By applying the Pontryagin Maximum Principle to this model, an iterative algorithm of solving the model is presented. The usability of the algorithm, including its convergence and effectiveness, is validated. Finally, the effect of a pair of controllable factors is inspected. This work initiates the study of patch testing-related issues through optimal control modeling.
防病毒(AV)软件开发相对于恶意软件发展的滞后性使得持续发布AV补丁成为必要。在实践中,一个AV补丁只有通过兼容性测试才能部署在组织的内联网上。在此背景下,可能会分配一部分主机来执行测试。被分配主机的比例随时间的函数被称为AV补丁测试(AVPT)策略,而从成本效益方面寻找令人满意的AVPT策略的问题被称为AVPT问题。本文通过最优控制建模来解决AVPT问题。通过纳入AV补丁测试的影响,引入了一种表征内联网期望状态演变的新数学模型。在此基础上,将AVPT问题建模为一个最优控制问题(AVPT模型)。通过将庞特里亚金极大值原理应用于该模型,提出了一种求解该模型的迭代算法。验证了该算法的可用性,包括其收敛性和有效性。最后,考察了一对可控因素的影响。这项工作通过最优控制建模开启了对补丁测试相关问题的研究。