Vulnerability discovery and mitigation in pharmaceutical continuous manufacturing networks

物联网联网设备和传感器在工业中的使用越来越多，这引发了人们对增加如此多未经适当研究的攻击媒介所带来的安全影响的担忧。我们希望找到在广泛的工业网络中检测安全漏洞的方法，重点是连续制造，并使用机器学习来减轻系统中恶意实体对所处理的整体数据的影响，并找到在恶意行为者存在的情况下验证数据和流程完整性的方法。

Increasing use of Internet of Things networked devices and sensors in industry leads to concerns about the security implications of adding so many attack vectors that have not been properly studied. We wish to find ways to detect security vulnerabilities in wide ranging industrial networks, with a focus on continuous manufacturing, and also to use machine learning to mitigate the impact of malicious entities in the system on the overall data processed and find ways to verify the integrity of data and processes in the presence of malicious actors.