Loss of Availability
Sensor data becomes unavailable, causing monitoring failure.
Industrial systems rely on trustworthy sensor data. When that data is manipulated, delayed, frozen, or degraded, the impact can reach safety, process stability, and operational reliability. CyberSense AI Guard was designed to show those risks in a practical and visual way.
The platform supports training, testing, demonstrations, and OT cybersecurity awareness through an interactive simulation environment.
Flammable gas detection for early warning of combustible gas leaks in industrial environments.
Natural gas monitoring used in pipelines and OT systems.
Air quality monitoring to detect harmful gases and anomalies.
Monitors thermal stability and detects overheating.
Tracks pressure for system safety and instability detection.
These scenarios show how cyber-attacks and sensor faults can affect OT visibility, integrity, safety, and stability.
Sensor data becomes unavailable, causing monitoring failure.
Data is manipulated, leading to incorrect system decisions.
Operators lose visibility into the real system state.
Operations continue under dangerous conditions without clear warning.
Erratic values can produce unstable control behavior and wrong responses.
A small issue spreads across multiple components and affects the wider system.
Sensor readings no longer match the true physical process conditions.
Inconsistent readings reduce trust in alerts, dashboards, and decisions.
Accumulated faults and attacks eventually prevent the system goal from being achieved.
The project can support awareness sessions, live demonstrations, and project exhibitions by making OT threats easier to understand through visuals and scenario-based explanation.
It also shows how browser-based and offline-first design can still support meaningful industrial security experiences.
This website was designed to be attractive to visitors, classmates, event guests, and anyone who wants a clear overview of the senior project without reading the full report first.