Wednesday, August 31, 2022

DDoS Sonification

Sonification presents data as sounds instead of visual charts. One of the best known examples of sonification is the representation of radiation level as a click rate in a Geiger counter. This article describes ddos-sonify, an experiment to see if sound can be usefully employed to represent information about Distributed Denial of Service (DDoS) attacks. The DDoS attacks and BGP Flowspec responses testbed was used to create the video demonstration at the top of this page in which a series of simulated DDoS attacks are detected and mitigated. Play the video to hear the results.

The software uses the Tone.js library to control Web Audio sound generation functionality in a web browser.

var voices = {};
var loop;
var loopInterval = '4n';
$('#sonify').click(function() {
  if($(this).prop("checked")) {
    voices.synth = new Tone.PolySynth(Tone.Synth).toDestination();
    voices.metal = new Tone.PolySynth(Tone.MetalSynth).toDestination();
    voices.pluck = new Tone.PolySynth(Tone.PluckSynth).toDestination();
    voices.membrane = new Tone.PolySynth(Tone.MembraneSynth).toDestination(); = new Tone.PolySynth(Tone.AMSynth).toDestination(); = new Tone.PolySynth(Tone.FMSynth).toDestination();
    voices.duo = new Tone.PolySynth(Tone.DuoSynth).toDestination();
    loop = new Tone.Loop((now) => {
  } else {
Clicking on the Convert charts to sound checkbox on the web page initializes the different sound synthesizers that will be used to create sounds and starts a timed loop that will periodically call the sonify() function convert current values of each of the metrics into sounds.
var metrics = [
  {name:'top-5-ip-flood', threshold:'threshold_ip_flood', voice:'synth'},
  {name:'top-5-ip-fragmentation', threshold:'threshold_ip_fragmentation', voice:'duo'},
  {name:'top-5-icmp-flood', threshold:'threshold_icmp_flood', voice:'pluck'},
  {name:'top-5-udp-flood', threshold:'threshold_udp_flood', voice:'membrane'},
  {name:'top-5-udp-amplification', threshold:'threshold_udp_amplification', voice:'metal'},
  {name:'top-5-tcp-flood', threshold:'threshold_tcp_flood', voice:'am'},
  {name:'top-5-tcp-amplification', threshold:'threshold_tcp_amplification', voice:'fm'}
var notes = ['C4','D4','E4','F4','G4','A4','B4','C5'];
function sonify(now) {
  var sounds = {};
  var max = {};
  metrics.forEach(function(metric) {
    let vals = db.trend.trends[];
    let topn = vals[vals.length - 1];
    let thresh = db.trend.values[metric.threshold];
    let chord = sounds[metric.voice];
    if(!chord) {
      chord = {};
      sounds[metric.voice] = chord;
    for(var key in topn) {
      let [tgt,group,port] = key.split(',');
      let note = notes[port % notes.length];
      chord[note] = Math.max(chord[note] || 0, Math.min(1,topn[key] / thresh));
      max[metric.voice] = Math.max(max[metric.voice] || 0, chord[note]);
  var interval = Tone.Time(loopInterval).toSeconds();
  var delay = 0;
  for(let voice in sounds) {
    let synth = voices[voice];
    let chord = sounds[voice];
    let maxval = max[voice];
    if(maxval) {
      let volume = Math.min(0,(maxval - 1) * 20);
      let note_array = [];
      for(let note in chord) {
        let val = chord[note];
        if((val / maxval) < 0.7) continue;
      let duration = Tone.Time(maxval*interval).quantize('64n');
      if(duration > 0) synth.triggerAttackRelease(note_array,duration,now+delay);
    delay += Tone.Time('16n').toSeconds();
The metrics array identifies individual DDoS metrics and their related thresholds and associates them with a sound (voice). The sonify() function retrieves current values of each of the metrics and scales them by their respective threshold. Each metric value is mapped to a musical note based on the TCP/UDP port used in the attack. Different attack types are mapped to different voices, for example, a udp_amplification attack will have a metallic sound while a udp_flood attack will have a percussive sound. Volume and duration of notes are proportional to the intensity of the attack.

The net effect in a production network is of a quiet rythm of instruments. When a DDoS attack occurs, the notes associated with the particular attack become much louder and drown out the background sounds. Over time it is possible to recoginize the distinct sounds on each type of DDoS attack.

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