Back in September, I was a guest on the IT Audit Labs Podcast!
I enjoyed my time talking with Joshua, Nick, and Eric about safety science and how we can apply lessons from safety to security. We covered a number of topics, including risk, ergonomics, culture, CrowdStrike and aviation, and I was pleasantly surprised to learn that Eric is a pilot!
You can find the episode on your favorite podcast service, or watch a video of the session on YouTube.
Description
Discover the vital intersection of safety science and cybersecurity, where human psychology meets technical innovation.
In this episode of The Audit, special guest John Benninghoff shares his expertise in safety science and how its principles can improve cybersecurity. From applying safety protocols in the tech industry to enhancing security culture through proactive human behaviors, we dive into a range of topics. Plus, we discuss how risk quantification and ergonomics can drive better security outcomes.
Cybersecurity, especially traditional security, has stagnated; adding security controls has appreciably improved outcomes and we continue to struggle with basic problems like vulnerabilities. Safety faced a similar problem 10-15 years ago; scientists and practitioners saw that safety outcomes were stagnant and concluded that the traditional method of avoiding accidents through centralized policies, procedures, and controls was no longer driving improvements.
I believe we’re seeing the same thing in security: historically, we’ve focused on constraining worker behavior to prevent cybersecurity breaches, and the limits of that approach are becoming increasingly clear. Adapting concepts from Safety Differently and Safety II offers a solution, by supporting success and focusing on positive capacities. In this talk, I will present practical advice on how to create a security program based on modern safety principles using evidence from both security and safety, and how it changes the role of the security professional.
Slides
My slides with notes, including references, are here.
Video
The talk was recorded, and if you attended the conference, you can watch the password-protected video here. (The password was shared with attendees)
SIRAcon 2024 wrapped up last Thursday, and once again the conference didn’t disappoint! We had an amazing line-up of speakers this year, and all of the talks were excellent! We also had a diversity of talks; academic and non-academic, quantitative and qualitative approaches, confidentiality and availability, technical and human risk. All but one of the talks were recorded and currently available to attendees on the conference website and will be available to members on the SIRA website after they are uploaded.
Once again, I was honored to be selected as a speaker, and my talk, “UnFAIR: Simplifying and Expanding Technology Risk Quantification,” was well received, and even generated some agreeable disagreement! While some disputed my assertion that FAIR (Factor Analysis of Information Risk) is not suited to risks outside of cybersecurity, I stand by my assertion: while FAIR can be used to quantify any risk, the language, once you get past the top level, is specific to the cybersecurity domain, and can be confusing for other types of risk, such as operational risk.
quantrr
In my talk, I presented a demo of a new Risk Quantification tool designed to be more flexible, use statistical distributions that better fit the data, and ultimately meet the needs of an analyst who is trying to start a risk quantification practice with limited time and no budget.
Since attendees expressed interest in trying out the tool, I wanted to make it more accessible, including to people with little or no experience using R. To address this, I spent time this week repackaging the demo and am excited to announce version 1.0 of quantrr (QUANT-R)! quantrr is bundled as an R package (library) and includes documentation on how to quickly get started using a “standalone” version and how to integrate quantrr into your existing R analysis and publishing workflow. Using the Quick Start instructions, you should be able to have an example report based on the demo up and running in less than an hour.
If you’ve learned FAIR or read Hubbard’s How to Measure Anything and want to get started quantifying risk with something other than Excel, give quantrr a try!
It’s very much an MVP release, by design, to get early reactions. I already have some things that I’d like to improve, and I would greatly appreciate feedback from any and all who give it a try, either sent to me directly or through GitHub. Reproducible bugs, feature requests, and pull requests are all welcome, I’d love to see it evolve into a community supported project and submitted to CRAN to become an official R package!
Slides
Slides from my talk are available here, and this is the link from the QR code I shared at the end.
