> For the complete documentation index, see [llms.txt](https://d3lab-dao.gitbook.io/pqv/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://d3lab-dao.gitbook.io/pqv/solution-pqv/probabilistic-qv.md).

# Probabilistic QV

## PQV Basic

Sybil attack is advantageous in QV because the more votes are divided, the more profitable it is. D3LAB suggests PQV which applies a probabilistic model so dividing votes always results in a loss.

![](https://632054869-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FiQ5WJUrQ6De8z8GO6PVJ%2Fuploads%2FPuJVgBxQl45m2KmX3tLr%2Fimage2.png?alt=media\&token=192ea059-3e2e-471c-b8dd-0ea2dea3db02)

Assume that the total number of votes is 100, and a user submitted 10 votes. There is a 10% ($$\frac{10}{100}$$) of chance that his opinion will be reflected, or a 90% ($$1-\frac{10}{100}$$)chance that it will not.

The expected value of voting in this condition is $$\sqrt{10}\times0.1\approx0.3162$$*. However if the user split the 10 votes in two, the expected value lowered to* $$\sqrt{5}\times2\times0.05\approx0.2246$$. This means doing Sybil attack is less beneficial.