Biblio

Supervisory control and data acquisition system is an important part of the country's critical infrastructure, but its inherent network characteristics are vulnerable to attack by intruders. The vulnerability of supervisory control and data acquisition system was analyzed, combining common attacks such as information scanning, response injection, command injection and denial of service in industrial control systems, and proposed an intrusion detection model based on graphical features. The time series of message transmission were visualized, extracting the vertex coordinates and various graphic area features to constitute a new data set, and obtained classification model of intrusion detection through training. An intrusion detection experiment environment was built using tools such as MATLAB and power protocol testers. IEC 60870-5-104 protocol which is widely used in power systems had been taken as an example. The results of tests have good effectiveness.

Supervisory control and data acquisition (SCADA) systems that run our critical infrastructure are increasingly run with Internet-based protocols and devices for remote monitoring. The embedded nature of the components involved, and the legacy aspects makes adding new security mechanisms in an efficient manner far from trivial. In this paper we study an anomaly detection based approach that enables detecting zero-day malicious threats and benign malconfigurations and mishaps. The approach builds on an existing platform (Bro) that lends itself to modular addition of new protocol parsers and event handling mechanisms. As an example we have shown an application of the technique to the IEC-60870-5-104 protocol and tested the anomaly detector with mixed results. The detection accuracy and false positive rate, as well as real-time response was adequate for 3 of our 4 created attacks. We also discovered some additional work that needs to be done to an existing protocol parser to extend its reach.