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DDoS Attack Expected Loss Estimator

This estimator calculates the expected annual loss from distributed denial-of-service (DDoS) attacks by combining expected attack frequency, probability of material disruption, and average financial impact per disruptive event. It separates frequency from severity so teams can update each assumption as threat conditions or architecture change.

Infrastructure, security, and risk teams can use the estimate to size mitigation budgets or compare hosting and protection options. The output is an expected-value measure, not a prediction of the number or cost of future attacks. It should be paired with high-impact scenarios because a low-frequency attack can still create a severe operational event.

Scenario inputs

attacks
%
USD
%
Result
—
Expected annual DDoS loss
Expected disruptive events—
Trend-adjusted frequency—
Loss per event—

1. Estimate annual attack frequency
Enter the number of meaningful DDoS attempts expected during a typical year.

2. Set disruption probability
Estimate the share of attempts likely to cause material service degradation or outage.

3. Value one disruptive event
Include downtime, response, lost transactions, service credits, and other nonduplicated losses.

4. Adjust for threat trend
Use a positive or negative percentage when you expect frequency to change from the baseline.

5. Review expected annual loss
Compare the result with mitigation cost and tolerance for severe events.

Adjusted Attack Frequency = Expected Attacks × (1 + Threat Trend Adjustment)

Expected Disruptive Events = Adjusted Attack Frequency × Disruption Probability

Expected Annual Loss = Expected Disruptive Events × Average Loss per Event

What the result means

The result is the average annual loss implied by the selected frequency, disruption probability, and event impact.

Because expected value can hide rare severe outcomes, also test a worst-plausible impact scenario.

Given:

  • Expected attacks: 8 per year
  • Material disruption probability: 25%
  • Average loss per disruptive attack: $90,000
  • Threat trend adjustment: 10%

Calculation:
Adjusted frequency = 8 × 1.10 = 8.8 attacks
Expected disruptive events = 8.8 × 0.25 = 2.2 events
Expected annual loss = 2.2 × $90,000 = $198,000

Result: The modeled expected annual DDoS loss is $198,000.

What is a material disruption?

Define it consistently, such as an outage exceeding a service threshold or causing measurable business loss.

Can attack frequency be fractional?

Yes. A value such as 0.5 represents one relevant attack every two years on average.

Should blocked attacks be included?

Include them in attack frequency only if the disruption probability reflects how often they still create material impact.

Why include a trend adjustment?

It lets the model modify a historical baseline for expected changes in exposure, traffic, adversary activity, or defenses.

How is this different from a downtime cost estimator?

Expected loss includes event frequency and probability. A downtime cost estimator focuses on the cost of a specific outage duration.