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Getting started with the Pepper project

This document gives an overview of the Pepper system. It assumes you've already installed the prerequisites; if you haven't, see README.md for a roadmap.

Directory organization

This repository has two main subdirectories:

  • compiler - This directory contains the front-end code; it turns source files in C or SFDL into sets of constraints suitable for execution by the back-end.

  • pepper - This directory contains the back-end code, the driver scripts, and the source code that gets compiled by the front-end.

Summary

  1. Write your program, storing it in apps/<program>.c.

  2. Follow the steps in the tutorial below, running the compilation and setup scripts for the prover and verifier, followed by input generation, proving, and verification.

  3. (optional) Customize the input generation function in input_generation/ and recompile the verifier binary, using the provided compilation script.

Tutorial and anatomy

(In this section, unless otherwise specified, directories are relative to pepper.)

  • Our example is matrix multiplication, which is in apps/mm_pure_arith.c. Open this file in your favorite text editor and change value ofSIZE on line 8 from 30 to 10 to make the execution faster. Then...

  • Next, we want to compile a C program to constraints, build the verifier and prover executables, and run the setup phase of the probabilistic proof protocol (which in this case is a SNARK, a kind of non-interactive argument). To this end, run the following in the pepper directory:

   ./pepper_compile_and_setup_V.sh mm_pure_arith mm_pure_arith.vkey mm_pure_arith.pkey
   ./pepper_compile_and_setup_P.sh mm_pure_arith
  • The first command will create verification_material/mm_pure_arith.vkey and proving_material/mm_pure_arith.pkey. If the verifier and prover are running on separate machines, you'll need to copy the proving key to the proving machine before proceeding.

  • Note that if the prover and verifier are running on the same machine, the C-to-constraints compiler will not be run twice! Additionally, only the verifier runs the setup (key generation) phase of the SNARK protocol.

  • Now generate some inputs to the computation:

    bin/pepper_verifier_mm_pure_arith gen_input mm_pure_arith.inputs
    

    (This command will create prover_verifier_shared/mm_pure_arith.inputs, which the prover will read in the next step. If the prover and verifier are running on separate machines, you'll need to arrange for the files in this directory to be shared between them.)

  • Run the prover:

  bin/pepper_prover_mm_pure_arith prove mm_pure_arith.pkey mm_pure_arith.inputs mm_pure_arith.outputs mm_pure_arith.proof
  • Run the verifier
  bin/pepper_verifier_mm_pure_arith verify mm_pure_arith.vkey mm_pure_arith.inputs mm_pure_arith.outputs  mm_pure_arith.proof

Some more details

Below, we detail each of the steps above.

apps/mm_pure_arith.c

This is the source code for the verified computation we wish to run. This code is compiled into a set of constraints, whose satisfying assignment is determined by the prover.

A few things to note here:

  1. The function compute() is the entry point for the computation. It takes two structs, struct In and struct Out, for arguments.

  2. The input and output struct definitions must be provided---they have no default definition.

  3. Preprocessor directives are allowed here. The search path for the preprocessor is ../compiler/cstdinc.

pepper_compile_and_setup_{V,P}.sh

  • Each of these shell scripts first calls the C-to-constraints compiler, and then builds verifier and prover executables in the bin/ directory. These exectuables are then run in setup mode.

  • For the verifier, this means running the key generation algorithm. Thus, the verifier setup script takes two arguments: filenames for the verification and proving keys, which are written to the verification_material and proving_material directories, respectively.

  • For the prover, setup is usually a no-op. The exception is for computations with remote storage - specifically, computations which make use of the Pantry PutBlock and GetBlock primitives. In this case the prover must initialize a database at setup time.

Input generation (input_generation/<computation>_v_inp_gen.h)

  • Before running the prover, you must create inputs to the computation of interest. This can be done either by running the verifier in "input generation" mode, or by creating an inputs file yourself. To run the verifier in input generation mode, type:
  bin/pepper_verifier_<program> gen_input <input filename>
  • Note that <computation>_v_inp_gen.h contains a computation-specific funtion which generates inputs to the computation, and is called by the verifier when running in input-generation mode. A default implementation which creates random inputs is generated from a template the first time the program is run, but it may be customized for more complicated input generation.

  • The verifier writes the inputs returned by this function to a file name you specify in the prover_verifier_shared/ directory. If you would like to use inputs from another source, you can skip running the input generation phase of the verifier and create this file yourself.

  • You will notice that the inputs are represented by an array, input_q[], while in mm_pure_arith.c they are represented by an arbitrary struct. The array corresponds to a "flattened" view of the struct in the order dictated by the struct's memory layout per the C standard.

Running the prover

  • To run a prover, type:
bin/pepper_prover_<program> prove <proving key filename> <input filename> <output filename> <proof filename>
  • The prover will look for (or create, in the case of outputs and proofs) the filenames you specify in proving_material (for the proving key), and prover_verifier_shared (for inputs, outputs and proof).

Running the verifier

  • To verify the results of a computation, type:
bin/pepper_verifier_<program> verify <verification key filename> <input filename> <output filename> <proof filename>
  • The verifier will look for the filenames you specify in verification_material (for the verification key), and prover_verifier_shared (for inputs, outputs, and proof).

bin/

  • In addition to the prover and verifiable executables, this directory contains the outputs of the C-to-constraints compiler, including a low-level representation of the constraints as a quadratic arithmetic program (QAP), and a prover worksheet instructing the prover on how to solve these constraints.

  • The format of these files is documented in fileformats.txt.

Advanced features

Private prover input

Pepper allows the prover to take inputs which are hidden from the verifier.

There are actually a couple of ways to do this. The most general is using the exo_compute function in your verifiable computation. You call it like any other C function, but the compiler treats it specially: when the prover is executing the program and solving the constraints, it will execute a user-provided program as a child process. This program can accept any input from the prover and return any output.

As a simple example, if you just want to have the prover take a fixed private key of some kind, the user-provided program can be a shell script that takes no input and echoes the data you want the prover to have.

See exo_compute.txt for more information.

Another option is using the commitment primitives (hashget() and commitmentget()), which allow the prover to provide the verifier with a commitment to some private state. This allows for more fine-grained control over what the prover's private inputs are allowed to be, but it does come with additional costs. https://eprint.iacr.org/2013/356.pdf, Section 6 provides the theoretical details. See apps/genome_snp_freq.c or apps/tolling.c for code examples.

Pantry

If you are using the Pantry PutBlock and GetBlock primitives, there are a couple extra requirements for your program:

  • You need to #include <db.h> in program.c.

  • You need to tell the verifier to initialize the blockstore. For an example of how to do this, see input_generation/ramput_micro_inp_gen.h or input_generation/ptrchase_merkle_inp_gen.h.

Buffet

  • If you want to run a computation with data-dependent loops, make sure to compile the llvm libraries needed for Buffet's C-to-C compiler first. (Run install_buffet.sh, or see compiler/buffetsm/README.md for more details.)

  • After you build the libraries, the compiler will be built and invoked automatically when compiling computations that include the [[buffet::fsm()]] compiler directive. See apps/rle_decode_flat.c for an example.)

Examples

  • Note, not all of the examples in apps/ have been tested in this release.

Known working ones include:

mm_pure_arith, pam_clustering, fannkuch, ptrchase_{benes,merkle}, mergesort_{benes,merkle}, boyer_occur_{benes,merkle}, kmpsearch, kmpsearch_flat, rle_decode, rle_decode_flat, sparse_matvec, sparse_matvec_flat.

Most others should work as well, but may require porting the verifier's input generation function from the main release.