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Single loss expectancy

As explained in Data-Driven Cybersecurity

Single loss expectancy is the estimated monetary loss resulting from one security incident or threat event.

Single loss expectancy (SLE) estimates the monetary loss from one security incident affecting a particular asset. Identify the asset, determine its asset value (AV), then estimate the exposure factor (EF): the percentage of that value the incident would destroy or compromise. section 6.3.2

SLE = AV x EF

Multiply asset value by exposure factor to estimate the loss from one incident. section 6.3.2

A stolen laptop

An encrypted stolen laptop might have an EF of 10% rather than 100% because encryption prevents data exposure. Its SLE would therefore be 10% of its asset value. The estimate depends on the incident and the controls in place. section 6.3.2

Check the EF before using SLE in a risk decision: damage, recoverability, backups, and other controls can change it. SLE can then be multiplied by annual rate of occurrence (ARO) to estimate annual loss expectancy (ALE). section 6.3.2

How Data-Driven Cybersecurity covers it

How deep it goes
Defines the calculation and explains how damage, recoverability, and controls affect its exposure-factor input.
Examples
Uses total data loss, short ransomware disruption, and an encrypted stolen laptop to illustrate differing exposure factors.
What it assumes
Introduces asset value and exposure factor as inputs, beginning with an identified asset.
What you can do after
Evaluate/understand it by estimating loss per incident and checking whether recovery and controls justify the exposure factor.
How it connects
Connects asset value and exposure factor to annual loss expectancy and annual rate of occurrence.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Data-Driven Cybersecurity. The section links point to the parts of the book it draws on.