Digital Eco[complex]systems vs Security Perturbations in Decentralization Manner
Digital Eco[complex]systems
If we’re going to talk about the digital ecosystem, then we need to talk about decentralization. Decentralization means all of the systems are a series of interconnected, hierarchal complex systems that are both chaotic and ordered.
It is important to note that decentralization is not a concept to be measured at all or nothing, and no system is completely decentralized. The question of how many different devices must be found in different locations to accept decentralization, and how many people or organizations would be sufficient to control the system, is similar to Sorites Paradox (The name “sorites” derives from the Greek word soros, meaning “pile” or “heap”) which tells us a single grain of wheat does not comprise a heap, nor do two grains of wheat, three grains of wheat, etc. However, at some point, the collection of grains becomes large enough to be called a heap, but there is apparently no definite point where this occurs.
The concepts of “decentralization” and “distributed” are the leading keywords used in defining the Blockchain. It is not clear what exactly these concepts used most often as synonyms. In fact, “decentralization is perhaps one of the worst words” according to Ethereum’s inventor Buterin.
“Blockchains are politically decentralized (no one controls them) and architecturally decentralized (no infrastructural central point of failure) but they are logically centralized (there is one commonly agreed state and the system behaves like a single computer)” — Buterin, as explained in his article
We’re not talking about a complicated system here. Conversely, we’re emphasizing the complex system that can show unexpected features and behavior that cannot be gleaned from the features and behaviors of the individual parts.
Digital ecosystems are complex systems!
Data is the operating currency of digital eco[complex]systems.
Distributed peer-to-peer networks are the conduits by which data at digital eco[complex]systems that are transformed and transported. Digital ecosystems are vehicles for data flows and consumption.
To understand digital eco[complex]systems, it is necessary to study not only parts and processes in isolation, but to study of a system’s organization is crucial since the behavior of the system’s parts is different in isolation than when working together as an integrated whole.
The whole is the emergent behaviors of the system that produces unpredictability. Yet, paradoxically, it is the combined behaviors and interactions of individual components that define behaviors of a system level, which means Decentralized Autonomous Organizations (DAO).
DAO into hierarchal structures is called emergent behavior. A self-organizing system (DAO) requires constant data exchange in order to exist. So that DAOs are open systems that operate far from equilibrium and rely on a continuous flux of information and services that are delivered from the outside by their connections with the system’s boundaries.
The DAO of a complex system with a unique behavior results from a network of many individuals each acting independently but following the same set of behavior rules that tell each individual how to respond to the relationship with its nearest neighbors.
In terms of Freedom vs Security
You cannot find a remedy in complex systems by around the idea of reductionism where it holds approaches that the behavior of a complex system is nothing more than the sum of its parts which relies upon the basic processes of observation, hypothesis, prediction test, and analysis.
You cannot describe any complex system such as a digital ecosystem by doing mathematical models, by simply using your logic, by soliciting the consensus of the public [1].
We can only see is an ongoing approximation. So, we can only consent the probability of occurrence more than the certainty. By allowing the possibility of occurring, the solution lies in the cause and effect relationships between components within the feedback mechanisms in complex systems.
To understand digital eco[complex]systems, we need to understand the ideas of nonlinearity and feedback. Feedback is a concept that is controlled by all complex systems. Feedback is also a driving force in the evaluation. So, feedback mechanisms produce resilience ecosystems.
Resilience is a measure of a system’s ability to survive and persist within a variable environment. Resilience arises from a combination of many feedback loops working together to restore a system after a large disruption. So, diversity produces this richness of feedback loops that serve to correct for outside disruptions.
A feedback loop is a mechanism by which change in a variable results in either an amplification (positive feedback) or a dampening (negative feedback) of that change. The self-regulation that results from individual feedback mechanisms is fundamental to the collective response in self-organizing systems.
As you know most real networks are social, technological, or ecological that is characterized by being a small world, clustered, and scale-free (power-law degree distribution).
Fractals can be described by a scale-free (power-law degree distribution) since the scale-free (complex) network model is a fractal shape. In nature, fractal objects have the property of being “self-similar” or “scale-free” in which their appearance is independent of the scale of observation and they are similar to itself independently of whether you look at them from near and from far.
The word fractal is used to describe patterns that exhibit self-similarity at different levels of magnification. One unifying factor is that fractals (self-similarity) and complex (scale-free) networks are an essential part of digital eco[complex]systems since they transport and transform the information.
Much like self-organization, self-similarity is a process that drives a new state from an old state using a set of fixed rules. In the case of self-similarity, the new state is a copy of the old state at a different level of magnification.
If the degree distribution of the complex system’s information flow network approximates a power-law (scale-free), then the network is more resilient to attack from the outside.
This is the secret to how certain ecosystems protect themselves.
Using analytical methods to describe this kind of network affords you the opportunity to define which parts on an ecosystem are vulnerable and which parts are resilient. We say that complex networks are resilient. If nodes with few connections are destroyed, the network will survive because most of the network’s connectivity is with the hubs.
Since there are many more nodes with few connections, the chance that a node with few connections being hit is much higher than the smaller frequency of hubs. The fact that there are a lot fewer of the more vulnerable hubs makes the network robust — or resilient to outside disturbance.
To enhance a system’s resilience, it is the hub that needs protection.
Security Dilemma
The reason why I feed you about complex systems inspired by Nature is that realizing the complex systems how to be resilient and enduring. There are six principles for longevity and resilience in both biology and business which are Redundancy, Diversity, Modularity, Adaption, Prudence, Embeddedness — according to strategist Martin Reeves [3].
As we increasingly face those more dynamic and unpredictable situations, we need to think more modestly and subtly about when and how we can shape, rather than control, unpredictable and complex situations. You have the surface barrier of the human skin, you have the very rapidly reacting innate immune system and then you have the highly targeted adaptive immune system. The point is, that if one system fails, another can take over, creating a virtually foolproof system.
An ecosystem with rich biodiversity is often a resilient system is built on diversity and redundancy as each unpredictable disturbance requires a different response. When one solution fails or performs poorly, others can step in to compensate [2].
Therefore, this is the motivation for survival.
It may be logical to raise the following question at this point: shouldn’t we take all possible security precautions early and seriously before the failures occur for the data that are sensitive to us? From my point of view, in fact, there is no question as to which is more accurate.
This is a continuously improving process that is optimized itself in a way of revealing the power and potential of our “natural paradigm — expressed in human terms –can be characterized by six interconnected, mutually-reinforcing elements: abundance, synergy, system, resilience, curiosity, and trust. [2]”
An approach to the using of technology after having securely mature enough, as a matter of fact, is our chronic problem in my sight, which is much more likely to lose ourselves in the security dilemma at every turn.
Resources:
[1] Re-Aligning with Nature: Ecological Thinking for Radical Transformation, 2016, Denise Kelly DeLuca
[2] Nature’s Patterns — Exploring Her Tangled Web, 2013, Bill Graham
[3] How to Build a Business That Lasts 100 Years by Martin Reeves — If you want to build a business that lasts, there may be no better place to look for inspiration than your own immune system. Take look at strategist Martin Reeves as he shares startling statistics about shrinking corporate lifespans and explains how executives can apply six principles from living organisms to build resilient businesses that flourish in the face of change.
