When I saw Jack Jones present on FAIR™ at an IANS Research Forum several years ago, it was like a light bulb went off in my head. I immediately ordered the FAIR book
As a graduate student exploring the emerging field of Behavioral Economics, or the science and art of judgment and decision-making, I have the unique opportunity to regularly draw from this study’s foundational concepts and directly apply them to communicate risk
“Don’t boil the ocean,” “manage expectations” and “baby steps” are common phrases that capture the mindset needed for consistent, sustained growth of a FAIR™ cyber risk quantification program. But every now and then it’s nice to get some quick wins to gain visibility and establish credibility within your organization.
After watching Prashanthi and Tony’s fireside chat at the 2021 FAIR Conference about getting a FAIR program started, I was struck by the simple and insightful themes that they kept repeating. Well, simple on paper, but not always easy to keep in mind when you’re in the thick of a FAIR rollout.
In an extensive white paper, Evan Wheeler, FAIR Institute Advisory Board Member and VP of Risk Management at Fintech firm NVDR, makes a strong case for the importance of data quality, integrity, and usability as core tenets of the data governance process
Ask a cyber risk professional about data governance practices, and they will likely tell you tales of classification schemes, access controls, and encryption … but we often overlook the importance of data quality, integrity, and usability that are core tenants of a robust data governance process.
In the first part of my blog post I focused on calculating the impact of a cybersecurity breach in relation to a company’s size and industry. In part two, I present an approach to better understand how often a company will experience security breaches.
Jack Whitsitt has been a FAIR practitioner since 2016, built the quantitative risk analysis program at Bank of America and is now doing the same at Datto (the services provider to MSPs)
In September, 2020, our IBM X-Force IRIS security analysis group began tracking strange phishing attacks targeting suppliers of HVAC equipment and services.
The generally accepted model for risk is that it is a function of frequency (some refer to it as probability or likelihood, i.e., how often the loss event will probably occur in a given time frame) and magnitude (how bad the event will probably be, consequences).
