Announcing: Data-driven Security Smashup

Data-driven Security Smashup

A Hackathon + Supercollider of Talent, Ideas, & Resources

Fall 2019

Las Vegas, NV; Saturday - Monday August 3-5, 2019

[updated June 14, 2019, see "RESET..." for more info]

• Venue: rented house*, well off the Strip Working on it.  Aiming for UNLV
• Timing: just before B-Sides LV/Black Hat/Defcon
• Organizers: Me, Jon Hawkes, plus 2-6 others to be named (interested? Contact me)
• On-site capacity: ~30 30 - 60
• Remote/virtual participation? Yes. Details TBD  Also several Satellite locations
• Call for Participation: coming soon, mid May
• Call for Sponsorship: coming soon, mid May
• Other locations: if this first Smashup goes well, we'd like to 'step-and-repeat' it soon in the EU, UK, Switzerland, elsewhere in US, and maybe more
• Updates and news:  follow @dds_smashup on Twitter

Summary

The Data-driven Security Smashup (DDS Smashup) is a combination of hackathon and ‘supercollider’ of talent, ideas, and resources, aiming for breakthrough innovations in data-driven cyber security, especially solutions to problems that span domains of people, process, technology, institutions, and culture.  

Why Is Breakthrough Innovation in Cyber Security So Hard?

Short answer: Innovation activities tend to focus on just a few pieces at a time, treating it as a simple problem. That doesn't create breakthroughs because the system* is too complicated.

* "system" = technology, information, people, processes, organizations, institutions, economics,...

In Sciences of the Artificial, Herbert Simon argued that most evolved systems (natural and artificial) were "partially decomposable" (if not fully decomposable) into units or subsystems that could be studied and understood in isolation. While cyber security is partially decomposable for many purposes, it is my conjecture that it is much less decomposable than we believe or desire.

What this means is that breakthrough innovations will depend on many, simultaneous inventions, including crossing system levels.

S Kauffman on Emergent Possibility Spaces in Evolutionary Biology, Economics, & Tech. (great lecture)

Below is a great lecture by Stuart Kauffman on the scientific and philosophical consequences of emergent possibility spaces in evolutionary biology and evolutionary economics, including technology innovation and even cyber security. This web page has the both video and lecture notes.

The lecture is very accessible anyone who reads books or watches programs on science aimed at the general public -- especially evolution, ecology, complexity, and innovation. He does mention some mathematical topics related to Newtonian physics and also Quantum Mechanics, but you don't need to know the details of any the math to follow his argument.  He gives very simple examples for all the important points he makes.

There are very important implications on epistemology (what do we know? what can be known?), scientific methods and research programs, and the causal role of cognition, conception, and creativity in economic and technological change. This last implication is an important element in my dissertation. I'll write more on that later.

Does a model and its data ever speak for themselves? No -- A reply to Turchin

This post is the first of a series to reply to Dr. Peter Turchin regarding his PNAS article (full text PDF -- free, thanks to Turchin & team), my letter to PNAS, and his PNAS letter reply.  I wrote a blog post here because I didn't think that Dr. Turchin's reply addressed my questions due to misunderstanding and I invited Dr. Turchin to engage in a colloquy via blog posts. I'm happy to say that Dr. Turchin wrote three blog posts (here, here, and here) in reply to my post, and this is my first reply.

While this post talks about interpreting simulation results, the general topic of data interpretation applies to all empirical research, and even data analysis in industry.