Preliminary Steps in Sonifying Web Log Data
Hall, David L.
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Detection of intrusions is a continuing problem in network security. Due to the large volumes of data recorded in Web server logs, analysis is typically forensic, taking place only after a problem has occurred. We are exploring the detection of intrusion signatures and patterns via an auditory display. Web log data is parsed and formatted using Python, then read as a data array by the synthesis language SuperCollider, which renders it as a sonification. This can be done either for the study of pre-existing data sets or in monitoring Web traffic in real time. Components rendered aurally include IP address, geographical information, and server Return Codes. Users can interact with the data, speeding or slowing the speed of representation (for pre-existing data sets) or “mixing” sound components to optimize intelligibility for tracking suspicious activity.