在作战与网络攻击结果审查软件（SONARR）及自主渗透测试系统（APTS）中引入验证器功能
Incorporation of Verifier Functionality in the Software for Operations and Network Attack Results Review and the Autonomous Penetration Testing System
AI总结：
针对SONARR与APTS中数字孪生事实值易变化、难持续匹配现实实体的问题，本文提出在SONARR中加入可核查现实状态、更新网络事实且支持任意脚本与动态参数的验证器，提升了软件输出的可靠性与一致性。
摘要：
作战与网络攻击结果审查软件（SONARR）和自主渗透测试系统（APTS）利用数字孪生网络中的事实与通用属性来表征现实世界实体。然而在部分场景中，事实值会定期变化，导致SONARR与APTS中的对象难以持续、准确地映射其对应的现实实体。本文提出并评估了在SONARR中新增验证器的方案，验证器负责核查现实世界状态并更新网络事实。加入验证器后，SONARR可从其运行环境中获取事实值并更新自身网络，提供了一套一致的方法来确保作战行动及相应结果与待评估的现实系统保持一致。验证器支持向SONARR常规作战行动中添加任意脚本与动态参数，由此带来的灵活性与一致性，可提升该软件输出的可靠性。
英文摘要：
The software for operations and network attack results review (SONARR) and the autonomous penetration testing system (APTS) use facts and common properties in digital twin networks to represent real-world entities. However, in some cases fact values will change regularly, making it difficult for objects in SONARR and APTS to consistently and accurately represent their real-world counterparts. This paper proposes and evaluates the addition of verifiers, which check real-world conditions and update network facts, to SONARR. This inclusion allows SONARR to retrieve fact values from its executing environment and update its network, providing a consistent method of ensuring that the operations and, therefore, the results align with the real-world systems being assessed. Verifiers allow arbitrary scripts and dynamic arguments to be added to normal SONARR operations. This provides a layer of flexibility and consistency that results in more reliable output from the software.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
