A general approach for measuring complexity and assessing its effects in generic systems. HBP Group & its partner, Ontonix, developed a novel solution suite for measuring complexity, entropy & resilience in systems. We have committed it to practice, defining a methodology and set of algorithms that treat systems as information sources and their observation as communication.

Plain English – We've taken theory that has been around for a long time (Shannon's Law) and figured out how to use it to measure complexity in all system, not just communication systems. That's a big deal because we get an objective quantitative complexity profile of the system. For example, the complexity profile of a counterfeit FPGA is different than a genuine FPGA (we've measured that). We think it's possible to also detect malware that is designed into chips, something we need to tackle in the future.

The complexity profile of a system changes over time. As complexity grows, the information transmission between system elements gets "noisy" increasing entropy (Shannon's Law). We measure and identify the "critical complexity level" of a system detecting when increasing "noise" is increasing fragility to a critical level. Think of a tachometer in a car, it doesn't predict when failure will happen but identifies a danger zone. Information exchange between elements in a system, growing complexity, noise & entropy, are properties that can be measured in all systems, e.g. project management, the electronic system of cars, air traffic control systems, critical infrastructures, and guidance systems of weapons platforms, etc.

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