Carnegie Mellon University's Yang Cai and colleagues have designed a method of making abnormal network traffic audible by rendering cybersecurity data musically.
The researchers explored several sound mapping algorithms, converting numeral datasets into music with diverse melodies, harmonies, time signatures, and tempos.
They produced music using network traffic data from an actual malware distribution network, and presented it to non-musicians, who could accurately identify pitch shifts when played on different instruments.
Said the researchers, "We are not only making music, but turning abstract data into something that humans can process."
Said Cai, “The process of sonification—using audio to perceptualize data—is not new, but sonification to make data more appealing to the human ear is.”
From Carnegie Mellon University CyLab Security and Privacy Institute
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