So Dave Mortman wrote: I don’t disagree with Adam that we need raw data. He’s absolutely right that without it, you can’t test models. What I was trying to get at was that, even though I would absolutely love to have access to more raw data to test my own theories, it just isn’t realistic [...]
Filed under: data by adam on Wednesday, September 30, 2009
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So awhile back, I posted the following to twitter: Thought of the Day: We don’t need to share raw data if we can share meta-data generated using uniform analytical methodologies. Adam, disagreed: @mortman You can’t test & refine models without raw data, & you can’t ask people with the same orientation to bring diverse perspectives. [...]
Filed under: data by David Mortman on Tuesday, September 29, 2009
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We can all learn from this great role model, aimed at personal nutrition awareness and education: Nutritiondata.com. If only security awareness web sites were this good.
Filed under: presentation, Uncategorized by Russell on Friday, September 25, 2009 | Social tagging: data visualization > visualization
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Politics and power can manipulate the “ground truth data” we depend upon. Case in point: the VP residence image on Google Earth is still blurred, even though VP Dick Cheney has been out of office for almost a year. Could similar things happen in InfoSec data if it were more visible and public? You bet.
Filed under: Amusements by Russell on Thursday, September 24, 2009
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I believe these are the final deliverables: National Cyber Leap Year Summit 2009 Co-Chairs Report — main discussion of metrics is p 26-28 National Cyber Leap Year Summit 2009 Participants’ Ideas Report – main discussion of metrics is p 44-46, p 50-51, and p 106; with related discussion on p 53-54. Also worth noting is [...]
Filed under: Uncategorized by Russell on Tuesday, September 22, 2009
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The SANS Top Cyber Security Risks report has received a lot of positive publicity. I applaud the effort and goals of the study and it may have some useful conclusions. We should have more of this. Unfortunately, the report has some major problems. The main conclusions may be valid but the supporting analysis is either confusing or weak. It would also be good if this study could be extended by adding data from other vendors and service providers.
Filed under: Data Analysis, presentation by Russell on Monday, September 21, 2009 | Social tagging: cyber security > SANS > top risks
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We can learn from bad visualization examples by correcting them. This example is from the newly released SANS “Top Cyber Security Risks” report. Their first graphic has a simple message, but due to various misleading visual cues, it’s confusing. A simplified graphic works much better, but they probably don’t need a graphic at all — a bulleted list works just as well. Moral of this story: don’t simply hand your graphics to a designer with the instructions to “make this pretty”. Yes, the resulting graphic may be pretty, but it may lose its essential meaning or it might just be more confusing than enlightening. Someone has to take responsibility for picking the right visualization metaphor and structures.
Filed under: presentation by Russell on Friday, September 18, 2009
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Over on their blog, the law firm announces yet another class action suit over a breach letter has been dismissed. Unfortunately, that firm is doing a fine business in getting rid of such suits. I say it’s unfortunate for two reasons: first, the sued business has to lay out a lot of money (not as [...]
Filed under: breach laws by adam on Friday, September 18, 2009
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Over on his Guerilla CISO blog, Rybolov suggests that we ask the Data.gov folks for infosec data using their Suggest a data set page. It sounds like a good idea to me! I took his request and built on it. Rather than breaking the flow with quotes and edit marks, I’ll simply say the requests [...]
Filed under: data by adam on Tuesday, September 15, 2009
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An “InfoSec risk scorecard” attempts to include all the factors that drive information security risk – threats, vulnerabilities, controls, mitigations, assets, etc. But for the sake of simplicity, InfoSec risk scorecards don’t include any probabilistic models, causal models, or the like. It can only roughly approximate it under simplifying assumptions. This leaves the designer open to all sorts of problems. Here are 12 tips that can help you navigate these difficulty. It’s harder than it looks.
Filed under: Data Analysis, presentation by Russell on Monday, September 14, 2009
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