Our publisher sent me a copy of Raffael Marty‘s Applied Security Visualization. This book is absolutely worth getting if you’re designing information visualizations. The first and third chapters are a great short intro into how to construct information visualization, and by themselves are probably worth the price of the book. They’re useful far beyond security. The chapter I didn’t like was the one on insiders, which I’ll discuss in detail further in the review.
In the intro, the author accurately scopes the book to operational security visualization. The book is deeply applied: there’s a tremendous number of graphs and the data which underlies them. Marty also lays out the challenge that most people know about either visualization or security, and sets out to introduce each to the other. In the New School of Information Security, Andrew and I talk about these sorts of dichotomies and the need to overcome them, and so I really liked how Marty called it out explicitly. One of the challenges of the book is that the first few chapters flip between their audiences. As long as readers understand that they’re building foundations, it’s not bad. For example, security folks can skim chapter 2, visualization people chapter 3.
Chapter 1, Visualization covers the whats and whys of visualization, and then delves into some of the theory underlying how to visualize. The only thing I’d change in chapter 1 is a more explicit mention of Tufte’s small multiples idea. Chapter 2, Data Sources, lays out many of the types of data you might visualize. There’s quite a bit of “run this command” and “this is what the output looks like,” which will be more useful to visualization people than to security people. Chapter 3, Visually Representing Data covers the many types of graphs, their properties and when they’re approprite. He goes from pie and bar charts to link graphs, maps and tree maps, and closes with a good section on choosing the right graph. I was a little surprised to see figure 3-12 be a little heavy on the data ink (a concept that Marty discusses in chapter 1) and I’m confused by the box for DNS traffic in figure 3-13. It seems that the median and average are both below the minimum size of the packets. These are really nits, it’s a very good chapter. I wish more of the people who designed the interfaces I use regularly had read it. Chapter 4, From Data to Graphs covers exactly that: how to take data and get a graph from it. The chapter lays out six steps:
- Define the problem
- Assess Available Data (I’ll come back to this)
- Process Information
- Visual Transformation
- View Transformation
- Interpret and Decide
There’s also a list of tools for processing data, and some comparisons. Chapter 5, Visual Security Analysis covers reporting, historical analysis and real time analysis. He explains the difference, when you use each, and what tools to use for each. Chapter 6, Perimeter Threat covers visualization of traffic flows, firewalls, intrusion detection signature tuning, wireless, email and vulnerability data. Chapter 7, Compliance covers auditing, business process management, and risk management. Marty makes the assumption that you have a mature risk management process which produces numbers he can graph. I don’t suppose that this book should go into a long digression on risk management, but I question the somewhat breezy assumption that you’ll have numbers for risks.
I had two major problems with chapter 8, Insider Threat. The first is claims like “fewer than half (according to various studies) of various studies involve sophisticated technical means” (pg 387) and “Studies have found that a majority of subjects who stole information…” (pg 390) None of these studies are referenced or footnoted, and this in a book that footnotes a URL for sendmail. I believe those claims are wrong. Similarly, there’s a bizarre assertion that insider threats are new (pg 373). I’ve been able to track down references to claims that 70% of security incidents come from insiders back to the early 1970s. My second problem is that having mis-characterized the problem, Marty presents a set of approaches which will send IT security scurrying around chasing chimeras such as “printing files with resume in the name.” (This because a study claims that many insiders who commit information theft are looking for a new job. At least that study is cited.) I think the book would have been much stronger without this chapter, and suggest that you skip it or use it with a strongly questioning bias.
Chapter 9, Data Visualization Tools is a guided tour of file formats, free tools, open source libraries, and online and commercial tools. It’s a great overview of the strengths and weaknesses of tools out there, and will save anyone a lot of time in finding a tool to meet various needs. The Live CD, Data Analysis and Visualization Linux can be booted on most any computer, and used to experiment with the tools described in chapter 9. I haven’t played with it yet, and so can’t review it.
I would have liked at least a nod to the value of comparative and baseline data from other organizations. I can see that that’s a little philosophical for this book, but the reality is that security won’t become a mature discipline until we share data. Some of the compliance and risk visualizations could be made much stronger by drawing on data from organizations like the Open Security Foundation’s Data Loss DB or the Verizion Breaches Report.
Even in light of the criticism I’ve laid out, I learned a lot reading this book. I even wish that Marty had taken the time to look at non-operational concerns, like software development. I can see myself pulling this off the shelf again and again for chapters 3 and 4. This is a worthwhile book for anyone involved in Applied Security Visualization, and perhaps even anyone involved in other forms of technical visualization.