Showing posts with label innovation. Show all posts
Showing posts with label innovation. Show all posts

Friday, June 14, 2019

RESET: "Data-driven Security Smashup" will launch in Fall 2019

Big change of plans for the "Data-driven Security Smashup":
We are canceling the live event in Las Vegas, August 3 - 5. 
Instead, we aim to launch one or more Virtual Smashup projects in the Fall of 2019, followed by one or more live events early in 2020, perhaps one in the US and one in UK.

Why?

Basically, we ran out of time as we were trying to organize the event: sponsorship, organizer recruiting and on-boarding, Call for Participation, legal structure, venue.  No fault to anyone.  We started relatively late, and our standards are high.  We didn't want to just throw it together and risk having things fall apart during the event.

Benefits

This new schedule gives us time to do it right, starting with the basics.  For example, we will secure a "fiscal sponsorship" relationship so we have the legal, financial, and operational infrastructure to take donations, manage risk, and to spend money responsibly.

Another "basic" that needs attention is contact and relationship management for all the people who have expressed interest, asked questions, or need responses.  This includes a dedicated website instead of this blog.

The new schedule gives us the lead time to recruit organizers and collaborators in academia, professional associations, industry, independent consultants, and government, both in US and internationally (mostly UK, Europe, Switzerland).

Personally, I'm not disappointed. The core idea is solid.  Lots of interest.  This change makes some space for some of my other priorities (dissertation!).

Stay tuned!

Monday, April 15, 2019

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.  

Sunday, April 14, 2019

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.

Monday, October 31, 2016

The Cyber Insurance Emperor Has No Clothes


(Of course, the title is hyperbole and attention-seeking. Now that you are here, I hope you'll keep reading.)

(click to enlarge)
In the Hans Christian Anderson story, The Emperor's New Clothes, the collective delusion of the Emperor's grand clothes was burst by a young child who cried out: "But he has got nothing on!"

I don't mean that cyber insurance has no value or that it is a charade.

My main point: cyber insurance has the wrong clothes for the purposes and social value to which it aspires.

This blog post sketches the argument and evidence. I will be following up separately with more detailed and rigorous analysis (via computational modeling) that, I hope, will be publishable.

tl;dr: (switching metaphors)
As a driving force for better cyber risk management, today's cyber insurance is about as effective as eating soup with a fork.
(This is a long post. For readers who want to "cut to the chase",  you can skip to the "Cyber Insurance is a Functional Misfit" section.)

Tuesday, June 21, 2016

Public Statement to the Commission on Enhancing National Cybersecurity, 6-21-2016

[Submitted in writing at this meeting. An informal 5 min. version was presented during the public comment period. This statement is my own and does not represent the views or interests of my employer.]

Summary

Cyber security desperately needs institutional innovation, especially involving incentives and metrics.  Nearly every report since 2003 has included recommendations to do more R&D on incentives and metrics, but progress has been slow and inadequate.

Why?

Because we have the wrong model for research and development (R&D) on institutions.

My primary recommendation is that the Commission’s report should promote new R&D models for institutional innovation.  We can learn from examples in other fields, including sustainability, public health, financial services, and energy.

What are Institutions and Institutional Innovation?

Institutions are norms, rules, and social structures that enable society to function. Examples include marriage, consumer credit reporting and scoring, and emissions credit markets.

Cyber security[1] has institutions today, but many are inadequate, dysfunctional, or missing.  Examples:
  1. overlapping “checklists + audits”; 
  2. professional certifications; 
  3. post-breach protection for consumers (e.g. credit monitoring); 
  4. lists of “best practices” that have never been tested or validated as “best” and therefore are no better than folklore.  

There is plenty of talk about “standards”,  “information sharing”, “public-private partnerships”, and “trusted third parties”, but these remain mostly talking points and not realities.

Institutional innovation is a set of processes that either change existing institutions in fundamental ways or create new institutions.   Sometimes this happens with concerted effort by “institutional entrepreneurs”, and other times it happens through indirect and emergent mechanisms, including chance and “happy accidents”.

Institutional innovation takes a long time – typically ten to fifty years.

Institutional innovation works different from technological innovation, which we do well.  In contrast, we have poor understanding of institutional innovation, especially on how to accelerate it or achieve specific goals.

Finally, institutions and institutional innovation should not be confused with “policy”.  Changes to government policy may be an element of institutional innovation, but they do not encompass the main elements – people, processes, technology, organizations, and culture.

The Need: New Models of Innovation

Through my studies, I have come to believe that institutional innovation is much more complicated  [2] than technological innovation.   It is almost never a linear process from theory to practice with clearly defined stages.

There is no single best model for institutional innovation.  There needs to be creativity in “who leads”, “who follows”, and “when”.  The normal roles of government, academics, industry, and civil society organizations may be reversed or otherwise radically redrawn.

Techniques are different, too. It can be orchestrated as a “messy” design process [3].  Fruitful institutional innovation in cyber security might involve some of these:
  • “Skunk Works”
  • Rapid prototyping and pilot tests
  • Proof of Concept demonstrations
  • Bricolage[4]  and exaptation[5]
  • Simulations or table-top exercises
  • Multi-stakeholder engagement processes
  • Competitions and contests
  • Crowd-sourced innovation (e.g. “hackathons” and open source software development)

What all of these have in common is that they produce something that can be tested and can support learning.  They are more than talking and consensus meetings.

There are several academic fields that can contribute defining and analyzing new innovation models, including Institutional Sociology, Institutional Economics, Sociology of Innovation, Design Thinking, and the Science of Science Policy.

Role Models

To identify and test alternative innovation models, we can learn from institutional innovation successes and failures in other fields, including:
  • Common resource management (sustainability)
  • Epidemiology data collection and analysis (public health)
  • Crash and disaster investigation and reporting (safety)
  • Micro-lending and peer-to-peer lending (financial services)
  • Emissions credit markets and carbon offsets (energy)
  • Open software development (technology)
  • Disaster recovery and response[6]  (homeland security)

In fact, there would be great benefit if there were a joint R&D initiative for institutional innovation that could apply to these other fields as well as cyber security.  Furthermore, there would be benefit making this an international effort, not just limited to the United States.

Endnotes

[1] "Cyber security" includes information security, digital privacy, digital identity, digital information property, digital civil rights, and digital homeland & national defense.
[2] For case studies and theory, see: Padgett, J. F., & Powell, W. W. (2012). The Emergence of Organizations and Markets. Princeton, NJ: Princeton University Press.
[3] Ostrom, E. (2009). Understanding Institutional Diversity. Princeton, NJ: Princeton University Press.
[4] “something constructed or created from a diverse range of available things.”
[5]  “a trait that has been co-opted for a use other than the one for which natural selection has built it.”
[6] See: Auerswald, P. E., Branscomb, L. M., Porte, T. M. L., & Michel-Kerjan, E. O. (2006). Seeds of Disaster, Roots of Response: How Private Action Can Reduce Public Vulnerability. Cambridge University Press.




Thursday, January 14, 2016

How fast does the space of possibilities expand? (replicating Tria, et al 2014)

How fast does the space of possibilities expand?  This question is explored in the following paper (free download):


From the abstract:
Novelties are a familiar part of daily life. They are also fundamental to the evolution of biological systems, human society, and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called “expanding the adjacent possible”. The dynamics of correlated novelties, however, have yet to be quantified empirically or modeled mathematically. Here we propose a simple mathematical model that mimics the process of exploring a physical, biological, or conceptual space that enlarges whenever a novelty occurs. The model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (Heaps' law) and for the probability distribution on the space explored (Zipf's law), as well as signatures of the process by which one novelty sets the stage for another.
I've written a NetLogo program to replicate their model, available here.  The code for the model is quite simple.  A majority of my code is for a "pretty layout", which is a schematic version of a "top-down view" of the urn.  Here's a video of a single run





Full screen with controls. (click to enlarge)
The charts on the top and center right show the frequency distribution by ball type (a.k.a. "color").  These are log-log plots, so a straight line (declining) is signature of a power law distribution, while a gradually curving (concave) is signature of lognormal or similar distribution with somewhat thinner tail.  Sharply declining curve is signature of a thin tailed distribution such as Gaussian.

So what?

This model will be useful in my dissertation because I need mechanisms to endogenously add novelty -- i.e. expand the possibility space based on the actions of agents in the simulated world, and not simply as external "shocks".

This is essential for modeling cyber security because some people claim that quantitative risk management is impossible in principle because of intelligent adversaries who can generate and exploit novel strategies and capabilities.


Tuesday, January 12, 2016

Institutional Innovation in Contested Territory: Quantified Cyber Security and Risk

Say you are an entrepreneurial sort of person who wants to really change the world of cyber security. Problem: nobody seems to know where the game-changing innovation is going to come from.  Is it technology?  Is it economics?  Is it law and policy? Is it sociology? Maybe combination, but what? And in what sequence?

If you aim for institutional innovation, then at some point you are going to need to take sides in the great "Quant vs. Non-quant" debate:
  • Can cyber security and risk be quantified? 
  • If "yes", how can quantitative information be used to realize security to significantly improve outcomes?
Whether you choose Quant or Non-quant, you will need some tools and methods to advance the state of the art.  But how do you know if you are choosing the right tools, and using them well?  (Think about the difference between Numerology and Calculus as they might be applied to physics of motion.)

Whoever makes sufficient progress toward workable solutions will "win", in the sense of getting wide-spread adoption, even if the other is "better" in some objective sense (i.e. "in the long run").

I examine this innovation race in a book chapter (draft). The book will probably come out in 2016.

Abstract:
"The focus of this chapter is on how the thoughts and actions of actors coevolve when they are actively engaged in institutional innovation. Specifically: How do innovators take meaningful action when they are relatively ‘blind’ regarding most feasible or desirable paths of innovation? Our thesis is that innovators use knowledge artifacts – e.g. dictionaries, taxonomies, conceptual frameworks, formal procedures, digital information systems, tools, instruments, etc. – as cognitive and social scaffolding to support iterative refinement and development of partially developed ideas. We will use the case of institutional innovation in cyber security as a way to explore these questions in some detail, including a computational model of innovation."
Your feedback, comments, and questions would be most welcome.

The computational model used is called "Percolation Models of Innovation".  Here is the NetLogo code of the model used in the book chapter.   Below are some figures from the book chapter.

Innovation as percolation. Progress moves from bottom to top. Each column is a "technology",
and neighboring columns are closely related.  This version (S&V 2005) only models
rate of progress and distribution of "sizes", not anything about the technology or
trajectory of innovation.
A screen shot of the user interface.  Three different models can be selected (upper left).

Thursday, August 27, 2015

Dissertation proposal: "Shaping Possibility Space"

At long last, I have submitted my dissertation proposal:
Fair warning: it is long -- 72 pages not including Glossary and Bibliography.  Being academic work, it will not be 'light reading' for many readers.  I have done my best to be clear and direct, but the subject matter is complicated.

Spoiler alert: I don't propose to solve the Cyber Security Problem(tm) in my research.  Instead, I'm studying the process of innovation that might, eventually, lead to new solutions, especially institutional innovations.  Some readers might find this boring, irrelevant, or 'ivory tower'.

Feedback is most welcome.  If you don't have my email address, ping me on Twitter.

The defense meeting is in mid-October.

Friday, October 31, 2014

Presentation: Topological View on Radical Innovation

I'm presenting today at the 6th Annual Complexity in Business Conference, sponsored by the University of Maryland Center for Complexity in Business.  Here are my slides.  (FYI: no information security content here, unless you are interested in institutional innovation.)

If you are really, really interested in this topic and want all the details and references, here is a paper I just completed for a Directed Reading class (89 pages, PDF).  It's a little rough around the edges due to time constraints.

Wednesday, June 25, 2014

My inputs to DHS on cyber economics & incentives

I'm at the 3rd day of Workshop on Economics of Information Security (WEIS) at Penn State.  The focus of this day is to provide input and ideas to the Science & Technology (S&T) Directorate in US Department of Homeland Security regarding R&D on cyber economics and incentives.

Here is the 2007 working paper I co-authored: "Incentive-based Cyber Trust -- A Call to Action".  I think many of the arguments and ideas are still relevant.  (It's long -- 27 pages -- but I think readers will be rewarded.)

Here are my slides.

Tuesday, March 25, 2014

RAND Report on Innovation in the Cybercrime Ecosystem

This is an excellent report -- well-researched and well-written -- on the growth and development of the cybercrime ecosystem:
Though it's sponsored by Juniper Networks, I don't see any evidence that the analysis or report were slanted.  This report should be useful for people in industry, government, and academia (a rare feat!).

While they do a broad survey of the cybercrime ecosystem, they examine botnets and zero-day exploit markets in detail.  What's important about this report is that it provides a thorough analysis of the innovation capabilities and trajectories in the cybercrime ecosystem.  This is vital to understand to guide investment decisions, architecture decisions, and R&D decisions beyond a 1 year time horizon.

Here's a timeline that documents the growing sophistication and innovation capability:

Black Market timeline (part 1) -- click to enlarge
Black Market timeline (part 2) -- click to enlarge




Sunday, March 16, 2014

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.

Monday, July 22, 2013

Call For Speakers: Cybersecurity Innovation Forum Jan 28-30 `14, Baltimore MD. Due 9/3/13

There's a new event that could be very important in to promote innovation in cyber security.
Cybersecurity Innovation Forum, Jan. 28-30, 2014, Baltimore MD
Call for Speakers, submissions due Sept. 3, 2013

There are four tracks, two slanted toward technical solutions and one slanted toward social/organizational solutions, and one mixed (see bold text):
  • Trusted Computing – Trust through device and system integrity 
  • Security Automation – Automate with trust to speed informed decision making 
  • Information Sharing – Openly and confidently share the information we need to share to make informed decisions and enact automated responses 
  • Research – Explore end-state research themes for designed-in security, trustworthy spaces, moving target, and cyber economic incentives.
I'm probably going to submit one or two proposals to the Research track. One might report on "How Bad Is It?" (breach impact estimation) and Ten Dimensions of Cyber Security Performance.  The second might be on the topic of innovative research models to improve industry-academic-government-citizen research collaboration, focusing on metrics, economics, social and organization aspects.

I'd also like to see a proposal from my brothers and sisters from SIRA on the state of the art in risk analysis and opportunities for research collaborations.

It would be great if this conference had good attendance from innovators in academia and industry.  It sure would help their cause if they had a strong cross-sector program committee.  That was one thing the National Cyber Leap Year folks got right.