Book Image

How to Measure Anything in Cybersecurity Risk

By : Douglas W. Hubbard, Richard Seiersen
Book Image

How to Measure Anything in Cybersecurity Risk

By: Douglas W. Hubbard, Richard Seiersen

Overview of this book

How to Measure Anything in Cybersecurity Risk exposes the shortcomings of current “risk management” practices, and offers a series of improvement techniques that help you fill the holes and ramp up security. In his bestselling book How to Measure Anything, author Douglas W. Hubbard opened the business world’s eyes to the critical need for better measurement. This book expands upon that premise and draws from The Failure of Risk Management to sound the alarm in the cybersecurity realm. Some of the field’s premier risk management approaches actually create more risk than they mitigate, and questionable methods have been duplicated across industries and embedded in the products accepted as gospel. This book sheds light on these blatant risks and provides alternate techniques that can help improve your current situation. You’ll also learn which approaches are too risky to save and are actually more damaging than a total lack of any security. Dangerous risk management methods abound; there is no industry more critically in need of solutions than cybersecurity. This book provides solutions where they exist and advises when to change tracks entirely.
Table of Contents (12 chapters)
Free Chapter
1
Foreword
2
Foreword
3
Acknowledgments
4
About the Authors
9
Index
10
EULA

Distribution Name: Truncated Power Law

Graph: horizontal axis of 0-5 million has descending curve that descends sharply to one million become stable, ends near four million, truncated limit marked at end. 90% marked for 0-2.

Figure A.7 Truncated Power Law Distribution

Parameters:

  • Alpha (Shape parameter)
  • Theta (Location parameter)
  • T (Truncated limit)

The truncated power law distribution mirrors the power law distribution, but with an upper limit that is imposed by the user. While the heavy tail of the power law distribution allows us to account for the rare catastrophic event, there may be a theoretical bound to the size of such an event. If this upper limit is not factored into the model, we may produce a misleading and unnecessarily grim forecast.

  • When to Use: The power law distribution should be truncated if an upper bound on the severity of an event is known.
  • Example: Losses of records may follow a power law but you know you only have a finite number of records to lose.
  • Excel Formula: =(alpha*theta^alpha/(x^(alpha+1)))/(1-(theta/T)^alpha)
  • Mean: =(alpha*theta/(alpha-1))