tidy repo

README.rst

@@ -3,12 +3,12 @@ Parameter curves for Concrete
 
 This Github repository contains the code needed to generate the Parameter curves used inside Zama. The repository contains the following files:
 
-- cpp/, Python scripts to generate a cpp file containing the parameter curves
+- cpp/, Python scripts to generate a cpp file containing the parameter curves (needs updating)
 - data/, a folder containing the data generated for previous curves. 
-- estimator/, Zama's internal version of the LWE Estimator
-- figs/, a folder containing various figures related to the parameter curves
-- scripts.py, a copy of all scripts required to generate the parameter curves
-- a variety of other python files, used for estimating the security of previous Concrete parameter sets
+- estimator_new/, the Lattice estimator (TODO: add as a submodule and use dependabot to alert for new commits)
+- old_files/, legacy files used for previous versions
+- generate_data.py, functions to gather raw data from the lattice estimator
+- verifiy_curves.py, functions to generate and verify curves from raw data
 
 .. image:: logo.svg
    :align: center
@@ -20,13 +20,16 @@ Example
 This is an example of how to generate the parameter curves, and save them to file.
 
 ::
-
-    sage: load("scripts.py")
-    sage: results = get_zama_curves()
-    sage: save(results, "v0.sobj")
+    ./job.sh
 ::
 
-We can load results files, and find the interpolants.
+This will generate several data files, {80, 96, 112, 128, 144, 160, 176, 192, 256}.sobj
+
+To generate the parameter curves from the data files, we run 
+
+`sage verify_curves.py`
+
+this will generate a list of the form:
 
 ::
 
@@ -41,22 +44,15 @@ We can load results files, and find the interpolants.
     (-0.014606812351714953, 3.8493629234693003, 256, 'PASS', 826)]
 ::
 
-Finding the value of n_{alpha} is done manually. We can also verify the interpolants which are generated at the same time:
+each element is a tuple (a, b, security, P, n_min), where (a,b) are the model 
+parameters, security is the security level, P is a boolean value denoting PASS or 
+FAIL of the verification, and n_min is the smallest reccomended value of `n` to be used.
 
-::
+Each model outputs a value of sigma, and is of the form:
 
-    # verify the interpolant used for lambda = 256 (which is interps[-1])
-    sage: z = verify_interpolants(interps[-1], (128,2048), 64)
-    [... code runs, can take ~10 mins ...]
-    # find the index corresponding to n_alpha, which is where security drops below the target security level (256 here)
-    sage: n_alpha = find_nalpha(z, 256)
-    653
-    
-    # so the model in this case is 
-    (-0.014327640360322604, 2.899270827311096, 653)
-    # which corresponds to
-    # sd(n) = max(-0.014327640360322604 * n +  2.899270827311096, -logq + 2), n >= 653
-::
+`f(a, b, n) = max(ceil(a * n + b), -log2(q) + 2)`
+
+where the -log2(q) + 2 term ensures that we are always using at least two bits of noise.
 
 Version History
 -------------------
@@ -67,6 +63,7 @@ Data for the curves are kept in /data. The following files are present:
 
     v0: generated using the {usvp, dual, decoding} attacks
     v0.1: generated using the {mitm, usvp, dual, decoding} attacks
+    v0.2: generated using the lattice estimator
 ::
 
 TODO List