This was my MSc Dissertation - Siren Songs: A Novel Method for Network Sonification. It was nominated for best dissertation of the year.
Network Sonification is the process of turning network data into sound. Specifically, sonification is about quantifiable and reproducible sound generation. Think of the geiger counter and how its sound represents levels of radiation. My network sonification process was designed to do the same.
The core process of the Siren Songs project was capturing packets on a network (or read from an existing capture file), analysing them individually and collectively, and based on certain thresholds and indicators this would then trigger set musical phrases that mapped to specific events on the network. I pushed these out as MIDI messages to allow any Digital Audio Workstation (DAW) to receive them and therefore allow easy customisation of the sounds played to find a useful mix of aesthetic sound design, meaningful alert to events, and hopefully a reduction in fatigue from the sounds played.
Over time I've moved away from network monitoring and cybersecurity in general - legacy of an older career - and toward the use of data for aesthetic purposes. I could see network packet interception or use of time-series open data sources as a means for generative composition sources for musicians, composers, and sound artists. Composing with or against data (and interpretations of it) seems ripe for an interesting clash between human creativity and our data streams.
Equally I have ideas for a project engaging with sonified sources of data in geographic mappings, drawing on the work of the likes of Hazzard et al. to compose soundtracks that represent e.g. the pollution and population data of cities overlaid on the location you are in, with the ability to scrub back and forth through time as well to hear how these changes have manifested in an emotional and sonically tangible way.