This shows you the differences between two versions of the page.
Both sides previous revision Previous revision | Next revision Both sides next revision | ||
sql-derivative-sensitivity-analyser_demo [2018/11/27 17:01] alisa [Running guessing advantage analysis] |
sql-derivative-sensitivity-analyser_demo [2018/11/27 17:01] alisa [Running sensitivity analysis] |
||
---|---|---|---|
Line 84: | Line 84: | ||
We are now ready to run the analysis. Click the blue button //Analyze//. Let us first set ε = 1 and β = 0.1. Click the green button //Run Analysis//. The most interesting value in the output that we see is the //relative error//. This can be interpreted as an upper bound on the relative distance of the noisy output from the actual output, which holds with probability 80%. There is unfortunately no strict upper bound on the additive noise, and it can potentially be infinite, though with negligible probability. Hence, we can only give a probabilistic upper bound on the noise, which is in our case hard-coded to 80%. | We are now ready to run the analysis. Click the blue button //Analyze//. Let us first set ε = 1 and β = 0.1. Click the green button //Run Analysis//. The most interesting value in the output that we see is the //relative error//. This can be interpreted as an upper bound on the relative distance of the noisy output from the actual output, which holds with probability 80%. There is unfortunately no strict upper bound on the additive noise, and it can potentially be infinite, though with negligible probability. Hence, we can only give a probabilistic upper bound on the noise, which is in our case hard-coded to 80%. | ||
- | We can now play around with the model and see how the error can be minimized. | + | We can now play around with the model and see how the error can be reduced. |
* Try to reduce β, e.g. try = 0.1. This does not affect security in any way, but may give smaller noise level. | * Try to reduce β, e.g. try = 0.1. This does not affect security in any way, but may give smaller noise level. | ||
* Try to reset scalings of //Table norm// to ''1.0'', or even try larger values. The error descreases, as we now consider smaller changes in the input (which means that we lose in security). | * Try to reset scalings of //Table norm// to ''1.0'', or even try larger values. The error descreases, as we now consider smaller changes in the input (which means that we lose in security). |