Tag Archives: causality

Causal Insulation

I just came across an essay by Wolter Pieters that complements my 2009 NSPW paper (mentioned here and here in this blog before) in style and content. In The (social) construction of information security (author’s version as PDF), Pieters discusses security in terms of causal insulation. This notion has its roots in Niklas Luhmann’s sociological theory of risk. Causal insulation means that to make something secure, one needs to isolate it from undesired causes, in the case of security from those that attackers would intentionally produce.On the other hand, some causes need to be allowed as they are  necessary for the desired functioning of a system.

I used a similar idea as the basis of my classifier model. A system in an environment creates a range of causalities—cause-effect relationships—to be considered. A security policy defines which of the causes are allowed and which ones are not, splitting the overall space into two classes. This is the security problem. Enforcing this policy is the objective of the security design of a system, its security mechanisms and other security design properties.

A security mechanism, modeled as a classifier, enforces some private policy in a mechanism-dependent space, and maps the security problem to this private space through some kind of feature extraction. In real-world scenarios, any mechanism is typically less complex than the actual security problem. The mapping implies loss of information and may be inaccurate and partial; as a result, the solution of the security problem by a mechanism or a suite of mechanisms becomes inaccurate even if the mechanism works perfectly well within its own reference model. My hope is that the theory of classifiers lends us some conceptual tools to analyze the degree and the causes of such inaccuracies.

What my model does not capture very well is the fact that any part of a system does not only classify causalities but also defines new causalities, I’m still struggling with this. I also struggle with practical applicability, as the causality model for any serious example quickly explodes in size.