General Motors is one of the world’s foremost designers and manufacturers of cars and trucks, which are sold in more than 125 countries. Headquartered in Detroit, GM operates almost 400 facilities on six continents.

The Internet of Things is an up-and-coming computer networking and data collection paradigm that utilizes many individual computers all working together towards a single goal.

GM’s manufacturing plants use the Internet of Things to increase efficiency and reduce errors in their manufacturing processes.

To protect their Internet of Things network, GM employs extensive real-time monitoring to alert them of any security threats or network malfunctions. As the Internet of Things network grows, the overhead of real-time monitoring increases, necessitating maximum efficiency.

Our tools for Profiling Manufacturing Plant Computer Network Traffic utilize machine learning techniques to efficiently identify potential network anomalies in GM’s manufacturing plants. Users can view the data and results of our monitoring in a web dashboard.

GM’s security analysts use our web dashboard to monitor and visualize the performance of the Internet of Things network. Any detected anomalies are ranked with a severity score, allowing the security analysts to solve the highest priority threats as soon as possible.

Our tools allow GM’s Internet of Things network to grow without sacrificing security or introducing expensive overhead.

Network flow data is stored in a MySQL database and our machine learning models are implemented in Python. These models are trained with network logs collected from multiple GM manufacturing plants. Users can interact with the system via a Tableau dashboard.