  The growing number of cyber-attacks against Industrial Control Systems (ICS)
in recent years has elevated security concerns due to the potential
catastrophic impact. Considering the complex nature of ICS, detecting a
cyber-attack in them is extremely challenging and requires advanced methods
that can harness multiple data modalities. This research utilizes network and
sensor modality data from ICS processed with a deep multi-modal cyber-attack
detection model for ICS. Results using the Secure Water Treatment (SWaT) system
show that the proposed model can outperform existing single modality models and
recent works in the literature by achieving 0.99 precision, 0.98 recall, and
0.98 f-measure, which shows the effectiveness of using both modalities in a
combined model for detecting cyber-attacks.
