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

增材制造在工业中的应用越来越多。航空航天和汽车工业的医疗假体和零件等安全关键产品正在通过增材制造方法进行打印，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运行取决于安全的嵌入式控制器，这些控制器可以监控和控制底层的物理制造过程。本研究将为网络物理工业增材制造基础设施研究一种完美的气隙入侵检测解决方案，其中一些控制器可能会被恶意代码感染。该研究将提供指导方针：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满足提高培训方法适用性的需要，以确保实物控制系统的安全和网络安全。活动将涉及女工程师协会和大量代表性不足和低收入的少数民族，他们具有不同的文化背景，并提高工业中现有的真实世界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，因此通常是控制器攻击的第一个目标。该项目将通过分析物理侧信道来研究非接触和完全空气间隙的入侵检测，以防止网络物理攻击。该解决方案不需要实时控制器上的运行时开销，只需对遗留系统进行最小的更改，并且即使目标系统完全受损也能可靠地识别入侵。这项工作将解决以下问题：i）在保持完美气隙的同时，对网络物理系统进行气隙入侵检测，ii）全面了解不同工业系统中可用于分析的侧通道类型，iii）对各种完美气隙入侵检测工具进行经验验证，包括独立和协同工作。

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.