Estimating Modulus

Use --param "logq" to estimate the modulus (logq) of the scheme.

The following commands estimate the modulus for a binary secret distribution, error distribution as a discrete Gaussian with standard deviation of 3.19, target security levels (lambda), and LWE dimensions:

python3 src/estimate.py --param "logq" --lambda "100" --n "1024" --secret "binary" --error "gaussian" --std "3.19"

Output Example

secret dist.   | lambda | lwe dim. | output
---------------+--------+----------+-------
Uniform (-1 0) | 100    | 1024     | 33

Show all estimations from formulas/numerical methods

When adding the option --table, the output shows the individual results for each of the formulas and numerical methods.

secret dist.   | lambda | lwe dim. | logq usvp | logq bdd | output
---------------+--------+----------+-----------+----------+-------
Uniform (-1 0) | 100    | 1024     | 33        | 33       | 33

Compare results against the Lattice Estimator

Use option -v, to see the result (columns est ‘name of attack / num’) of running the Lattice Estimator with the given parameters and compare them with our formulas/numerical methods.

secret dist.   | lambda | lwe dim. | logq usvp | est usvp | logq bdd | est bdd | output
---------------+--------+----------+-----------+----------+----------+---------+-------
Uniform (-1 0) | 100    | 1024     | 33        | 103      | 33       | 101     | 33