CPS: Medium: Collaborative Research: Trustworthy Cyber-Physical Additive Manufacturing with Untrusted Controllers

增材制造在工业上的应用越来越广泛。安全关键产品，如医疗假体和航空航天和汽车行业的零件，正在通过增材制造方法打印，但目前还没有标准方法来验证所生产零件的完整性。工业增材制造的可靠操作依赖于安全的嵌入式控制器，该控制器监视和控制底层物理制造过程。本研究将研究一种完美的气隙入侵检测解决方案，用于网络物理工业增材制造基础设施，其中一些控制器可能被恶意代码感染。该研究将为以下方面提供指导：i)将软件安全、控制系统设计和信号处理中的弹性解决方案结合在一起；ii)将可靠和实用的网络物理攻击检测纳入现实世界的制造中。教育和技术转让活动将解决提高培训方法适用性的需求，以确保物理控制系统的安全和网络安全。活动将涉及女性工程师协会和具有不同文化背景的大量未被充分代表的低收入少数群体，并提高工业中现有的、现实世界的增材制造系统的安全性。下一代网络物理增材制造能够实现先进的产品设计和功能，但越来越依赖于高度网络化的工业控制系统，这为网络攻击提供了机会。防御这些威胁的主要方法依赖于位于相同目标控制器内的基于主机的入侵检测器，因此它们通常是控制器攻击的第一个目标。本计划将透过分析物理旁道，研究非接触及完美气隙入侵侦测，以防范网路物理攻击。该解决方案不需要实时控制器的运行时开销，只需要对遗留系统进行最小的更改，并且即使目标系统完全被破坏，也能可靠地识别入侵。这项工作将解决以下问题：i)在网络物理系统上进行气隙入侵检测，同时保持完美的气隙；ii)全面了解可用于不同工业系统分析的侧通道类型；iii)对各种完美的气隙入侵检测工具进行经验验证，无论是独立的还是协同工作的。

Additive manufacturing is finding increased application in industry. Safety-critical products, such as medical prostheses and parts for aerospace and automotive industries are being printed by additive manufacturing methods, but there currently are no standard methods for verifying the integrity of the parts that are produced. Trustworthy operation of industrial additive manufacturing depends on secure embedded controllers that monitor and control the underlying physical manufacturing processes. This research will investigate a perfectly air-gapped intrusion detection solution for cyber-physical industrial additive manufacturing infrastructures in which some of the controllers may be infected by malicious code. The research will provide guidelines to: i) tie together resilience solutions in software security, control system design, and signal processing, and ii) incorporate reliable and practical cyber-physical attack detection into real-world manufacturing. Educational and technology transfer activities will address the need to improve the applicability of training methods to ensuring the safety and cyber security of physical control systems. Activities will involve The Society of Women Engineers and a large population of underrepresented and low-income minorities with diverse cultural backgrounds and improve the security of existing, real-world, additive manufacturing systems in industry. Next generation cyber-physical additive manufacturing enables advanced product designs and capabilities, but increasingly relies on highly networked industrial control systems that present opportunities for cyber attacks. The predominant approach to defending against these threats relies on host-based intrusion detectors that sit within the same target controllers, and hence are often the first target of the controller attacks. This project will research contact-less and perfectly air-gapped intrusion detection by analyzing physical side-channels to protect against cyber-physical attacks. This solution requires no runtime overhead on real-time controllers, requires minimal change to legacy systems, and reliably identifies intrusions even if the target system is completely compromised. The work will address solutions for: i) air-gapped intrusion detection on cyber-physical systems while maintaining a perfect air gap, ii) a comprehensive understanding of the types of side-channels available for analysis in different industrial systems, and iii) empirical validation of the various perfectly air-gapped intrusion detection tools, both independently and working in tandem.