I-Corps: An Investigation of the Commercial Potential of Cyber-physical Security for Advanced Manufacturing Systems

这一i-Corps项目的广泛影响/商业潜力将为制造业提供一种方法，以实时识别和检测其生产环境中的网络物理攻击。目前，制造业正在运行的生产系统容易受到恶意攻击，这可能会导致生产的零部件不符合预期的设计要求。这种偏离设计意图的行为可能会导致产品损坏、失去客户信任，并可能伤害员工和/或客户。采用拟议的方法将确保制造商免受网络物理攻击，并创建强大的供应链。这将允许制造商继续为普通公众和国防工业生产敏感零部件，增加了恶意攻击影响零部件生产的难度。通过成功完成这个项目，i-Corps团队将通过指导研究生并与美国各地的制造商讨论网络物理安全来进一步提高这方面的意识。这个i-Corps项目使用传统的决策分析和数据分析技术来识别和检测制造系统中的恶意事件。这是通过两个阶段的方法来完成的。首先，完成网络物理漏洞评估，突出生产环境中易受恶意攻击的区域。利用决策树和流程映射，脆弱性评估用于提供制造设施的网络物理复原力的高级别概述。其次，提出的检测方法包括一个气隙传感器套件，它可以放置在任何关键设备上，以实时检测恶意事件。建议的方法分析与机器无关的侧通道测量，如功耗、振动和声音，以识别过程中的异常。通过执行漏洞评估和实施建议的传感器套件，可以确保整个生产设施免受旨在降低部件质量和/或破坏生产部件的恶意网络物理攻击。这一裁决反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project will provide the manufacturing industry with an approach to identify and detect cyber-physical attacks within their production environments in real-time. Currently, the manufacturing industry is operating production systems vulnerable to malicious attacks, which may cause produced parts to not meet intended design requirements. Such a deviation from design intent could result in damaged products, loss of customer trust, and potentially injure employees and/or customers. The adoption of the proposed approach will secure manufacturers from cyber-physical attacks and create a strong supply chain. This will allow manufacturers to continue to produce sensitive parts both for the general public and the defense industry, increasing the difficulty of a malicious attack to affect part production. Through successful completion of this program, the I-Corps team will further develop awareness in this area through mentoring graduate students and discussing cyber-physical security with manufacturers across the United States.This I-Corps project employs both traditional decision analysis and data analysis techniques to identify and detect malicious events within manufacturing systems. This is done through a two-phase approach. First, a cyber-physical vulnerability assessment is completed which highlights areas within the production environment susceptible to malicious attack. Employing decision trees and process mapping, the vulnerability assessment is used to provide a high level overview of the cyber-physical resiliency of a manufacturing facility. Second, the proposed detection approach consists of an air-gapped sensor suite which can be placed on any piece of critical equipment to detect malicious events in real-time. The proposed approach analyzes side-channel measurements independent of the machine such as power consumption, vibration, and sound to identify anomalies within the process. Through performing the vulnerability assessment and implementing the proposed sensor suite, the entire production facility can be secured from malicious cyber-physical attacks intended to reduce part quality and/or sabotage produced parts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.