Human Interface for Cyber Security Anomaly Detection Systems
Low-level network traffic information is often times beyond the understanding of common system operators (Byte counts, port numbers, packet data, etc.). However, anomaly based Intrusion Detection Systems (IDS) often provide such low-level, difficult to comprehend information. This paper details a Human Interface for Security Awareness (HISA) algorithm for interpreting cyber incident information to human operators from anomaly based intrusion detections systems. A similarity algorithm mapping anomaly results to signature based intrusion system rules is developed. Categorizations of attacks found in rules created for the Snort intrusion system were used as a basis of information to present to the user.