Shadowband Systems Inc.

ShadowDC Demos

The demos below are actual screen captures of ShadowDCTM in use.  All demos require the Flash plug-in.

This example illustrates the use of a sniffer feeding into a crisp rule set (SNORT rules) that feeds into an output array reflecting matched (1) or unmatched (0) values.  Code generation is also demonstrated.

This example demonstrates the use of the following:
  • Traffic sniffer feeding into a crisp rule set
  • A Crisp Rule Set that feeds into a scripting block (supports python, perl, and javascript)
  • A Scripting block that feeds into a fuzzy inference block
  • A Fuzzy Inference block that feeds into an output block to store the results.
  • The logging feature is demonstrated as well.

This example has the following components:
  • Traffic sniffer that feeds into a scripting block
  • A scripting block that feeds a data mining block acting as a classifier
  • A data mining block that feeds both into an output block and a scripting block
  • An additional scripting block that feeds into a plotter.

This example illustrates the use of an evolutionary algorithm with the following components:
  • A traffic sniffer that feeds into a crisp rule set
  • A crisp rule set that feeds into an evolutionary algorithm
  • An evolutionary algorithm feeding into an output block

This example illustrates the use of a fuzzy inference block that is fed traffic from a sniffer.  The code generation feature is demonstrated by generating the code for the sniffing as well as the fuzzy inference engine.

This example demonstrates the use of the genetic algorithm block.  This input is a data stream and the output of the genetic algorithm is fed into an output array.

The neural block is composed of subsystems of various layers of linear, recurrent and biased.  the output of which is sent to an data array output block.

Feel free to contact us if you have a demo request or a question about the demos above.

Shadowband Systems Inc.
One Meca Way
Norcross, GA 30093
678.228.5066