复杂系统支持设备的网络安全风险测量与评估

Christopher J. Guerra, C. Camargo
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引用次数: 1

摘要

复杂系统的漏洞足迹包括许多可能危及数据完整性、系统功能、飞行价值和可用性的潜在向量。通过引入带有“钩子”的硬件,入侵点可能会在系统部署前数年发生,以应对未来的攻击。对于使用通用操作系统的支持设备,恶意设备占用的空间更大。与支持设备接触或接近接触的用户数量放大了复杂系统的脆弱性。并非所有支持设备都有数字或软件组件。虽然纯机械装置的网络安全风险较低,但它们也不能幸免。通常,它们是使用自动测试设备制造或翻新的,这可能会影响到支持设备的性能,导致难以察觉的缺陷。我们描述了一种测量和评估复杂系统或复杂系统舰队网络安全风险的方法,以响应与系统接口的支持设备足迹。这种方法结合了来自两个关键数据库的信息。第一个数据库描述了包括支持设备在内的子系统之间的信息流和接口。第二个数据库描述了攻击支持设备的关键、开放式接口点。关键参数可以包括操作系统的类型、公开端口的数量及其类型,以及无线接口的存在。我们为子系统受损的情况定义了影响参数。同样,我们根据标准为支持设备定义风险参数,该标准是支持设备中使用的技术的易感性的函数。与可靠性分析一样,我们构建了子系统与保障设备之间的关系网络。我们可以计算一个给定的支持设备项目对子系统或整个系统的二维风险影响关系。这种方法可以扩展到计算车队级别的风险和对所有支持设备的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring and Assessing the Cybersecurity Risk of Support Equipment to Complex Systems
The vulnerability footprint for complex systems includes many potential vectors for compromising the data integrity, system functionality, flight worthiness, and availability. The point of intrusion could occur years prior to fielding the system through the introduction of hardware with “hooks” for a future attack. For support equipment with common operating systems, the footprint available to those with hostile intent is greater. The quantity of users which have contact or near contact with the support equipment amplifies the vulnerability of the complex system. Not all support equipment has a digital or software component. While purely mechanical fixtures have a lower cybersecurity risk, they are not immune. Often they are manufactured or refurbished using automatic test equipment which could be affected resulting an imperceptible defect in the support equipment's performance. We describe a methodology to measure and assess the cybersecurity risk of complex system or a fleet of complex systems in response to the support equipment footprint, which interfaces with the system. This approach combines information from two key databases. The first database characterizes the information flow and interfaces between the subsystems to include the support equipment. The second database describes the critical, open-ended interface points for an attack against the support equipment. The critical parameters can include the type of operating system, the number of exposed ports and their types, and the presence of wireless interfaces. We define impact parameters for the case where a subsystem is compromised. Similarly, we define risk parameters for the support equipment based on criteria which is a function of the susceptibility of the technology employed within the support equipment. As in reliability analyses, we construct a network of the relationships between the subsystems and the support equipment. We can compute the two-dimensional risk-impact relationship for a given support equipment item to the subsystem or to the complete system. This approach can be extended to compute a fleet level risk and impact for all of the support equipment.
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