What is Cyber-Physical System (CPS)?
Cyber-physical system (CPS) refers to integrated systems that combine computing, networking, and physical processes. These systems rely on sensors, networks, and actuators to monitor and control physical environments, such as in industrial automation, smart grids, and healthcare devices. In the context of data security, CPS involves protecting both the cyber and physical components from threats. Ensuring the security of CPS includes safeguarding data integrity, preventing unauthorized access, and protecting against disruptions that could impact physical operations. Effective security measures for CPS are critical to maintaining the reliability and safety of these interconnected systems.
Examples of Cyber-Physical Systems
- Smart Manufacturing: Industrial IoT (IIoT), predictive maintenance, robotics, digital twins
- Autonomous Vehicles: Real-time decision-making based on sensors, AI, and navigation systems
- Smart Cities: Traffic control, smart grids, water distribution systems
- Healthcare Systems: Robotic surgery, connected medical devices, remote diagnostics
- Aerospace and Defense: Advanced avionics, UAVs, real-time mission control
Key Components of CPS
Component | Description |
|---|---|
Sensors | Collect real-time data from the physical environment (e.g., temperature, motion, pressure) |
Actuators | Perform physical actions based on control commands (e.g., motors, valves, robotic arms) |
Embedded Systems | Process sensor data and issue control signals |
Network Infrastructure | Enable communication between devices, controllers, and cloud systems |
Control Algorithms | Automate decision-making for physical responses (e.g., adjust speed, optimize energy use) |
Human-Machine Interfaces (HMI) | Allow users to interact with or override the system when necessary |
Why CPS Matters
CPS transforms traditional systems into intelligent, automated, and interconnected networks — enabling:
Greater efficiency and precision in operations
Real-time data-driven decision-making
Autonomous and adaptive control
Integration of AI, machine learning, and cloud computing
Scalable monitoring across large or remote physical environments
