Abstract:
An apparatus and method of displaying a network security situation is provided. The apparatus includes an extraction unit configured to classify a characteristic factor including IP addresses of a transmission node and a reception node from a traffic flow, a network visualization unit configured to generate a domain circle visualizing each of a transmission domain and a reception domain as a circle shape by mapping the IP addresses of the transmission node and the reception node to points on circumference as one to one, arrange the generated domain circle on an axis, and visualize each of a transmission network area and a reception network area as a sphere shape, a session construction unit configured to a session of the visualized transmission network area and reception network visually, and a display unit configured to display the session which is visually constructed.
Abstract:
An abnormal traffic detection apparatus and method based on Modbus communication pattern learning is provided. The abnormal traffic detection apparatus based on the Modbus communication pattern learning previously detects and responds to abnormal traffic on a Modbus/TCP protocol. According to the present invention, a communication service between control systems can be stably provided by previously detecting the abnormal traffic capable of interfering with a stable operation of the control system. Particularly, since the effective abnormal traffic on the Modbus/TCP protocol can be previously detected, security of the control system can be increased by rapid detection and response with respect to security threats on the Intranet of the control system, and availability can be secured.
Abstract:
Provided are a system and method for detecting an abnormal behavior of a control system by analyzing flows of the control system. Flow information of the control network is collected, and flows are classified according to the collected flow information and a flow group is generated. An abnormal behavior of the control system is detected by analyzing flows of the generate flow group. That is, internal systems of the control network are grouped according to functions, and a situation of a system of a group performing the same function is managed to thus quickly detect an abnormal behavior of the control system.