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Category Archives: Information Security

Secure360 (@Secure360) Data Analysis & Visualization Talk Resources #Sec360

Many thanks to all who attended the talk @jayjacobs & I gave at @Secure360 on Wednesday, May 15, 2013. As promised, here are the [slides](https://dl.dropboxusercontent.com/u/43553/Secure360-2013.pdf).

We’ve enumerated quite a bit of non-slide-but-in-presentation information that we wanted to aggregate into a blog post so you can vi[sz] along at home. If you need more of a guided path, I strongly encourage you to take a look at some of the free courses over at [Coursera](https://www.coursera.org/).

For starters, here’s a bit.ly bundle of data analysis & visualization bookmarks that @dseverski & I maintain. We’ve been doing (IMO) a pretty good job adding new resources as they come up and may have some duplicates to the ones below.

People Mentioned

– [Stephen Few’s Perceptual Edge blog](http://www.perceptualedge.com/) : Start from the beginning to learn from a giant in information visualization
– [Andy Kirk’s Visualising Data blog](http://www.visualisingdata.com/) (@visualisingdata) : Perhaps the quintessential leader in the modern visualization movement.
– [Mike Bostock’s blog](http://bost.ocks.org/mike/) (@mbostock) : Creator of D3 and producer of amazing, interactive graphics for the @NYTimes
– [Edward Tufte’s blog](http://www.edwardtufte.com/tufte/) : The father of what we would now identify as our core visualization principles & practices.
– [Nathan Yau’s Flowing Data blog](http://flowingdata.com/) : Making visualization accessible, practical and repeatable.
– [Data Stories Podcast](http://datastori.es/) : Yes, you can learn much about data visualization from an audio podacst (@datastories)
– [storytelling with data](http://www.storytellingwithdata.com/) (@storywithdata) : Extremely practical blog by Cole Nussbaumer that will especially help folks “stuck” in Excel
– [Jay’s blog](http://beechplane.wordpress.com/)
– [My {this} blog](http://rud.is/b)

Tools Mentioned

– [R](http://www.r-project.org/) : Jay & I probably use this a bit too much as a hammer (i.e. treat every data project as a nail) but it’s just far too flexible and powerful to not use as a go-to resource
– [RStudio](http://www.rstudio.com/) : An *amazing* IDE for R. I, personally, usually despise IDEs (yes, I even dislike Xcode), but RStudio truly improves workflow by several orders of magnitude. There are both desktop and server versions of it; the latter gives you the ability to setup a multi-user environment and use the IDE from practically anywhere you are. RStudio also makes generating [reproducible research](http://cran.r-project.org/web/views/ReproducibleResearch.html) a joy with built-in easy access to tools like [kintr](http://yihui.name/knitr/).
– [iPython](http://ipython.org/) : This version of Python takes an already amazing language and kicks it up a few notches. It brings it up to the level of R+RStudio, especially with it’s knitr-like [iPython Notebooks](http://ipython.org/ipython-doc/dev/interactive/htmlnotebook.html) for–again–reproducible research.
– [SecViz](http://secviz.org/) : Security-centric Visualization Site & Tools by @raffaelmarty
– [Mondrian](http://www.theusrus.de/Mondrian/) : This tool needs far more visibility. It enables extremely quick visualization of even very large data sets. The interface takes a bit of getting used to, but it’s faster then typing R commands or fumbling in Excel.
– [Tableau](http://www.tableausoftware.com/) : This tool may be one of the most accessible, fast & flexible ways to explore data sets to get an idea of where you need to/can do further analysis.
– [Processing](http://processing.org/) : A tool that was designed from the ground up to help journalists create powerful, interactive data visualizations that you can slipstream directly onto the web via the [Processing.js](http://processingjs.org/) library.
– [D3](http://d3js.org/) : The foundation of modern, data-driven visualization on the web.
– [Gephi](https://gephi.org/) : A very powerful tool when you need to explore networks & create beautiful, publication-worthy visualizations.
– [MongoDB](http://www.mongodb.org/) : NoSQL database that’s highly & easily scaleable without a steep learning curve.
– [CRUSH Tools by Google](https://code.google.com/p/crush-tools/) : Kicks up your command-line data munging.

Slopegraph As A Service

@adammontville [posited](http://www.tripwire.com/state-of-security/it-security-data-protection/quick-thoughts-on-verizons-dbir-and-20-critical-security-control-mappings/) that Figure 15 from this year’s [DBIR](http://www.verizonenterprise.com/DBIR/2013/) could use some slopegraph love. As I am not one to back down from a reasonable challenge, I obliged.

Here’s the original chart (produced by @jayjacobs):

figure15-orig

and, here’s a _very_ _quick_ slopegraph version of it:

figure15-slope

You can click on both/either for a larger version. If I had more time, I could have made the slopegraph version nicer, but it conveys a story fairly well the way it is, especially with the highlight on the two biggest changes between 2008 & 2012.

Two problems with the modified visualization are (a) multi-column slopegraphs blend into a [parallel coordinate](http://www.juiceanalytics.com/writing/parallel-coordinates/) or plain old line graph pretty quickly (thus, reducing their slopegraph-y goodness); and, (b) the diversity of the year-over-year DBIR data set makes the comparison between years almost pointless (as the DBIR itself points out).

I also generated a proper/traditional slopegraph, comparing 2008 to 2012:

figure15-true-slope

The visualization is far more compact and, if the goal was to show the change between 2008 and 2012, it provides a much clearer view of what has and has not changed.

Wait Wait…Don’t Pwn Me! (SOURCE Boston) Transcript & Thank You!

wwdpm.001For those that wanted to play along at home, I’ve cleaned up the text and made the Wait Wait…Don’t Pwn Me! closing segment of SOURCE Boston 2013 available for download [PDF]. The video crew had cameras running, so keep checking the @SOURCEconf web site as it’ll probably get posted as they crank through all of the conference session videos (give them time, tho, as there are a ton of vids to process).

I also wanted to, again, thank @selenakyle for her most excellent job playing Carl Kasell; the awesome panelists: @451Wendy, @innismir & @andrewsmhay; @joshcorman for—yet again—putting up with me picking on him (and getting all the questions right); and our volunteers: @ra6bit, @Gmanfunky (and three more who I need Twitter handles from :-).

I only hope that @petersagal & the WWDTM crew can forgive me if they ever read the transcript or views the video of the segment.

SOURCE Boston (@SOURCEConf) Data Analysis & Visualization Talk Resources #srcbos13

Many thanks to all who attended the talk @jayjacobs & I gave at @SOURCEconf on Thursday, April 18, 2013. As promised, here are the [slides](https://dl.dropboxusercontent.com/u/43553/SOURCE-Boston-2013.pdf) which should be much less washed out than the projector version :-)

We’ve enumerated quite a bit of non-slide-but-in-presentation information that we wanted to aggregate into a blog post so you can viz along at home. If you need more of a guided path, I strongly encourage you to take a look at some of the free courses over at [Coursera](https://www.coursera.org/).

For starters, here’s a bit.ly bundle of data analysis & visualization bookmarks that @dseverski & I maintain. We’ve been doing (IMO) a pretty good job adding new resources as they come up and may have some duplicates to the ones below.

People Mentioned

– [Stephen Few’s Perceptual Edge blog](http://www.perceptualedge.com/) : Start from the beginning to learn from a giant in information visualization
– [Andy Kirk’s Visualising Data blog](http://www.visualisingdata.com/) (@visualisingdata) : Perhaps the quintessential leader in the modern visualization movement.
– [Mike Bostock’s blog](http://bost.ocks.org/mike/) (@mbostock) : Creator of D3 and producer of amazing, interactive graphics for the @NYTimes
– [Edward Tufte’s blog](http://www.edwardtufte.com/tufte/) : The father of what we would now identify as our core visualization principles & practices.
– [Nathan Yau’s Flowing Data blog](http://flowingdata.com/) : Making visualization accessible, practical and repeatable.
– [Jay’s blog](http://beechplane.wordpress.com/)
– [My {this} blog](http://rud.is/b)

Tools Mentioned

– [R](http://www.r-project.org/) : Jay & I probably use this a bit too much as a hammer (i.e. treat ever data project as a nail) but it’s just far too flexible and powerful to not use as a go-to resource
– [RStudio](http://www.rstudio.com/) : An *amazing* IDE for R. I, personally, usually despise IDEs (yes, I even dislike Xcode), but RStudio truly improves workflow by several orders of magnitude. There are both desktop and server versions of it; the latter gives you the ability to setup a multi-user environment and use the IDE from practically anywhere you are. RStudio also makes generating [reproducible research](http://cran.r-project.org/web/views/ReproducibleResearch.html) a joy with built-in easy access to tools like [kintr](http://yihui.name/knitr/).
– [iPython](http://ipython.org/) : This version of Python takes an already amazing language and kicks it up a few notches. It brings it up to the level of R+RStudio, especially with it’s knitr-like [iPython Notebooks](http://ipython.org/ipython-doc/dev/interactive/htmlnotebook.html) for–again–reproducible research.
– [SecViz](http://secviz.org/) : Security-centric Visualization Site & Tools by @raffaelmarty
– [Mondrian](http://www.theusrus.de/Mondrian/) : This tool needs far more visibility. It enables extremely quick visualization of even very large data sets. The interface takes a bit of getting used to, but it’s faster then typing R commands or fumbling in Excel.
– [Tableau](http://www.tableausoftware.com/) : This tool may be one of the most accessible, fast & flexible ways to explore data sets to get an idea of where you need to/can do further analysis.
– [Processing](http://processing.org/) : A tool that was designed from the ground up to help journalists create powerful, interactive data visualizations that you can slipstream directly onto the web via the [Processing.js](http://processingjs.org/) library.
– [D3](http://d3js.org/) : The foundation of modern, data-driven visualization on the web.
– [Gephi](https://gephi.org/) : A very powerful tool when you need to explore networks & create beautiful, publication-worthy visualizations.
– [MongoDB](http://www.mongodb.org/) : NoSQL database that’s highly & easily scaleable without a steep learning curve.
– [CRUSH Tools by Google](https://code.google.com/p/crush-tools/) : Kicks up your command-line data munging.

Bahrain eGov Conference “Risk Reality” Slides

For those finding this post from the Bahrain eGov conference, I’d like to re-extend a hearty “Thank you!” for being one of most engaging, interactive and intelligent audiences I’ve ever experienced. I truly enjoyed talking with all of you.

You can find the slides on my Dropbox [PDF] and please do not hesitate to bounce any questions here or on Twitter (@hrbrmstr).

Off to Bahrain

Screenshot_4_8_13_8_03_AM

As a result of a prod by @djbphaedrus I’m off to the Bahrain International eGovernment Forum this week to host a two hour workshop on “information risk reality”. As a result, blogging & tweeting will be at significantly reduced levels, so enjoy the brief respite from my blatherings while you can :-)

If you happen to be in Bahrain while I’m there, drop me a note and I’m sure I can find time between Tuesday night and Thursday afternoon to say hello!

It’s Never About The Security…

it's about the people…

it’s about the people… (click for clip)

A Wish for Snow in Spring

The basic technique of cybercrime statistics—measuring the incidence of a given phenomenon (DDoS, trojan, APT) as a percentage of overall population size—had entered the mainstream of cybersecurity thought only in the previous decade. Cybersecurity as a science was still in its infancy, as many of its basic principles had yet to be established.

At the same time, the scientific method rarely intersected with the development and testing of new detection & prevention regimens. When you read through that endless stream of quack cybercures published daily on the Internet and at conferences like RSA, what strikes you most is not that they are all, almost without exception, based on anecdotal or woefully inadequately small evidence. What’s striking is that they never apologize for the shortcoming. They never pause to say, “Of course, this is all based on anecdotal evidence, but hear me out.” There’s no shame in these claims, no awareness of the imperfection of the methods, precisely because it seems to eminently reasonable that the local observation of a handful of minuscule cases might serve the silver bullet for cybercrime, if you look hard enough.


But, cybercrime couldn’t be studied in isolation. It was as much a product of the internet expansion as news and social media, where it was so uselessly anatomized. To understand the beast, you needed to think on the scale of the enterprise, from the hacker’s-eye view. You needed to look at the problem from the perspective of Henry Mayhew’s balloon. And you needed a way to persuade others to join you there.

Sadly, that’s not a modern story. It’s an adapted quote from chapter 4 (pp. 97-98, paperback) of The Ghost Map, by Steven Johnson, a book on the cholera epidemic of 1854.

I won’t ruin the book nor continue my attempt at analogy any further. Suffice it to say, you should read the book—if you haven’t already—and join me in calling out for the need for the John Snow of our cyber-time to arrive.