The elevators at an international airport are connected to the internet for support and monitoring reasons. To ensure this system is robust against cyber attacks our client monitors the internet traffic that reaches the elevator.
Detecting and preventing cyber attacks
When there’s a cyber attack the data stream shows different patterns, however it’s difficult to predict what these patterns will look like and due to the volume of data it’s impossible for humans to manually monitor it.
Taking an unsupervised machine learning approach
Using an unsupervised machine learning approach we created a robust, scalable model to detect changes in the data stream that fall outside of the regular pattern.
Increasing security and reducing operational costs
Over 500 elevators can now be monitored by one Security Officer and the Officer will only need to investigate the elevator data more closely when an anomaly is detected.