Coder Social home page Coder Social logo

nexus-tyf / wbmatrix Goto Github PK

View Code? Open in Web Editor NEW
16.0 3.0 12.0 74.01 MB

https://github.com/scnucrypto/WBMatrix

License: Apache License 2.0

CMake 0.16% C++ 2.89% C 94.45% Python 2.49%
whitebox wbaes wbsm4 matrix-library linear-encoding affine-transformation invertible-matrix

wbmatrix's Introduction

WBMatrix

An Optimized Matrix Library for White-Box Block Cipher Implementations.

Contains the matrix operations related to the white-box block cipher implementation and provides thorough test cases for their performance and accuracy. The test cases also include the Chow et al.'s white-box AES and Xiao-Lai's white-box SM4 implementations built by WBMatrix, NTL, and M4RI, respectively.

Applications

  1. CEJO White-box AES

  2. Table Redundancy Method for White-box AES

  3. Xiao-Lai White-box SM4

  4. Xiao-Lai White-box AES

  5. Improved Masking for White-box AES

  6. WBMatrix based LowMC

  7. Bai-Wu White-box SM4

  8. WSISE White-box SM4

Clone

$ git clone --depth 1 https://github.com/Nexus-TYF/WBMatrix

Matrix Library

Supports For Following Operations (4/8/16/32/64/128/256 bits)

  • Matrix-Vector multiplication.
  • Matrix-Matrix multiplication.
  • Generation of an invertible Matrix with its inverse matrix (pairwise invertible matrices).
  • Generation of the pairwise invertible affine transformations.
  • Matrix transpositon.
  • Affine transformation.
  • Encodings concatenation.
  • Encodings conversion.

Header Files

  • WBMatrix.h The declaration of the main functions.
  • struture.h Data structure of the matrix and affine functions.
  • random.h The declaration of the random functions.

Main Functions (8bit in Example)

  • affineU8(Aff8 aff, uint8_t arr) affine transformation for an uint8_t number arr, and returns an uint8_t result.
  • affinemixM8(Aff8 aff, Aff8 preaff_inv, Aff8 *mixaff) affine conversion between aff and preaff_inv, result is set in mixaff.
  • affinecomM8to32(Aff8 aff1, Aff8 aff2, Aff8 aff3, Aff8 aff4, Aff32 *aff) affine concatenation, the matrix part of aff consists of the submatrices on its diagonal, while the vector part of aff consists of the subvectors.
  • copyM8(M8 Mat1, M8 *Mat2) replicates the matrix Mat1 to Mat2.
  • flipbitM8(M8 *Mat, int i, int j) flips the (i, j) bit in matrix Mat.
  • genMatpairM8(M8 *Mat, M8 *Mat_inv) generates an invertible matrix Mat and its inverse matrix Mat_inv.
  • genaffinepairM8(Aff8 *aff, Aff8 *aff_inv) generates an affine transformation aff and its inversion aff_inv.
  • identityM8(M8 *Mat) converts the matrix Mat into an identity matrix.
  • invsM8(M8 Mat, M8 *Mat_inv) calculates the inversion of Mat by Gaussian elimination method, result is set in Mat_inv.
  • isinvertM8(M8 Mat) determines if the matrix is invertible (1 for positive).
  • MatMulVecM8(M8 Mat, V8 Vec, V8 *ans) multiplication between a matrix Mat and a vertor Vec, result is set in ans.
  • MatMulNumM8(M8 Mat, uint8_t n) multiplication between a matrix Mat and a number n, returns a number.
  • MatMulMatM8(M8 Mat1, M8 Mat2, M8 *Mat) multiplication between a matrix Mat1 and a matrix Mat2, result is set in Mat.
  • MatAddMatM8(M8 Mat1, M8 Mat2, M8 *Mat) addition between the matrix Mat1 and Mat2, result is set in Mat.
  • MattransM8(M8 Mat, M8 *Mat_trans) transpositon for a matrix Mat, result is set in Mat_trans.
  • readbitM8(M8 Mat, int i, int j) extracts the (i, j) bit in matrix Mat, returns 0/1.
  • setbitM8(M8 *Mat, int i, int j, int bit) assigns the (i, j) bit a value bit (0/1).
  • initM8(M8 *Mat) converts all the elements of the matrix Mat into 0.
  • randM8(M8 *Mat) generates a random matrix Mat.
  • printbitM8(M8 Mat) prints all the elements of the matrix Mat.
  • isequalM8(M8 Mat1, M8 Mat2) determines if the matrix Mat1 is equal to Mat2 (1 for positive).
  • initV8(V8 *Vec) converts all the elements of the vector Vec into 0.
  • randV8(V8 *Vec) generates a random vector Vec.
  • VecAddVecV8(V8 Vec1, V8 Vec2, V8 *Vec) addition between the vector Vec1 and Vec2, result is set in Vec.
  • HWU8(uint8_t n) calculates the Hamming Weight of a number n.

Code Examples

M8 mat[3]; //defines an 8-bit matrix.
genMatpairM8(&mat[0], &mat[1]); //generates the pairwise invertible matrices.
MatMulMatM8(mat[0], mat[1], &mat[2]); //matrix-matrix multiplication.
printM8(mat[2]); //prints the matrix.

Included library

  1. RandomSequence

Test Cases

Folder Introduction

  • github1_M4RI The performance test for matrix operation and for the generation of the pairwise invertible matirces by M4RI library.
  • github(x) The performance test for the generation of an invertible matrix or the computation of its invertion by the implementations on Github.
  • NTL The performance test for matrix operation and for the generation of the pairwise invertible matirces by NTL library.
  • randomness A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications (NIST Special Publication 800-22 Revision 1a).
  • WBAES A Chow et al.'s white-box AES implementation and its performance test built by WBMatrix, NTL, and M4RI respectively.
  • WBSM4 A Xiao-Lai's white-box SM4 implementation and its performance test built by WBMatrix, NTL, and M4RI respectively.

File Introduction

  • Accuracy_test.c Accuracy test for the matrix operations in WBMatrix.
  • BasisMatrixMethod_test.c Performance test for the generation of the pairwise invertible matrices by Basis Matrix Method.
  • LowMCMethod_text.cpp Performance test for the generation of the pairwise invertible matrices by LowMC Method and Gaussian Elimination method.
  • RGEMethod_test.c Performance test for the generation of the pairwise invertible matrices by Reverse Gaussian Elimination Method and Gaussian Elimination method.
  • RLUDMethod_test.c Performance test for the generation of the pairwise invertible matrices by Reverse LU Decomposition Method and Gaussian Elimination method.
  • WBGEMethod_test.c Performance test for the generation of the pairwise invertible matrices by Randomly Generate and Verify Method and Gaussian Elimination method.
  • WBMatrixMatOp_test.c Performance test for the matrix operations in WBMatrix.
  • WBMatrixMethod_test.c Performance test for the generation of the pairwise invertible matrices by WBMatrix Method.

Build

$ mkdir build
$ cd build
$ cmake ..
$ make

Run

$ ./WBMM

Included libraries

  1. NTL
  2. M4RI
  3. SMx-SM4
  4. WhiteBoxAES
  5. sp800_22_tests
  6. Inverse-matrix
  7. Inverse-Matrix
  8. parallelMatrixInversion
  9. InvertibleMatrix
  10. Inverse-of-Matrix
  11. inverseMatrix
  12. lowmc

Last Updated : 2021/09/29
WBMatrix Version: 3.3.1


Upgrade history:
(2019/12/9)

  1. Added: An invertible matrix is generated from an initialized matrix (now just supports for 8/32bits operations).
  2. Fixed: Unifies the API.
  3. Added: The adjustable generation times in inverse.h.
  4. Added: Uses initinvbaseM(8/32)() function to generate an initialized invertible matrix and its trails are recorded in basetrailM(8/32).
    8bits default value is 10,
    32bits default value is 30,
    which represent the operation times.
  5. Added: If not use the initialized function then each matrix is generated from an identity matrix with the default times.
  6. Added: Copy function to replace the identify function.

(2019/12/10)

  1. Added: 16/64/128bits inverse matrix functions.
    New method has been covered.

(2019/12/11)

  1. Added: 16/64bit affine transformation.
  2. Added: 128bit affine transformation.
    No retrun value because of its special structure.

(2019/12/12)

  1. Added: 16/64/128bit affine combination operation.

(2019/12/16)

  1. Added: the header files for a defination of the matices.

(2019/12/17)

  1. Fixed: Error fixes.
  2. Added: The parameters for initializing the intermediate matrix function.
    inverse.h has the max times and min times for selection.

(2020/01/08)

  1. Added: Matrix addition function.

(2020/01/10)

  1. Improved: File tidying.
  2. Added: WBMatrix test.
  3. Added: Matrix Basis Method test.

(2020/01/12)

  1. Added: 128bit test for matrix basis method.

(2020/01/18)

  1. Added: Updates the test case of the generation of an invertible matrix and the computation of its inverse matrix.
  2. Added: Invertible funcions: Matrix Basis Method, WBMatrix Method, Reverse Gaussian Elimination Method.
  3. Added: Inverse functions: WBMatrix Method, Matrix Basis Method.

(2020/01/20)

  1. Added: CMakeLists.txt
  2. Added: M4RI Method.

(2020/01/21)

  1. Improved: Organizes file structure, especially fixs the structure.h and .c errors.

(2020/01/22)

  1. Improved: Deletes xor.h.

(2020/01/30)

  1. Added: Gaussian elimination Method (Based on WBMatrix).
  2. Improved: Changes the generation function of a random Matrix.

(2020/01/31)

  1. Added: Reverse LU Decomposition Method.

(2020/02/01)

  1. Improved: Functions for the generation of a random matrix.

(2020/02/02)

  1. Added: Comparison test on github.
  2. Added: Accuracy Test.
  3. Improved: Parameter Orders of the affinemix function.

(2020/02/07)

  1. Fixed: Multipe defination of the global variables.
  2. Added: Function for random seed.
  3. Added: WBAES.

(2020/02/09)

  1. Fixed: Poor randomness of the random matrix function.
  2. Added: Function for estimating the invertibility of a matrix.

(2020/02/16)

  1. Added: New test cases from github.

(2020/03/05)

  1. Added: Performance test cases of M4RI: basic arithmetic with matrix.
  2. Added: Performance test cases of NTL.
  3. Added: Performance test cases of WBMatrix.

(2020/03/06)

  1. Added: Vector addition funcion.
  2. Fixed: Accuracy test mode.
  3. Improved: Replaces the rotation with a logical-AND.

(2020/03/07)

  1. Added: WBAES by M4RI.

(2020/03/09)

  1. Added: WBAES by WBMatrix.

(2020/03/10)

  1. Added: WBSM4 by M4RI.
  2. Fixed: The release version of WBAES (WBMatrix version).
  3. Added: WBSM4 by WBMatrix.

(2020/03/11)

  1. Added: WBSM4 by NTL.
  2. Improved: Clean-up NTL files.

(2020/03/15)

  1. Added: Release on github.

(2020/04/15)

  1. Added: Supports for returning Hamming Weight.
  2. Added: An example for mitigating DCA attack.

(2020/06/22)

  1. Added: The references of the articles and implementations.
  2. Fixed: Errors of the random function in Linux.

(2020/06/25)

  1. Added: Randomness test cases (Special Publication 800-22 Revision 1a).

(2020/07/01)

  1. Fixed: Updates the random functions.

(2020/07/31)

  1. Added: Updates the new method for generating the pairwise invetible matrices.
  2. Added: Bitwise operation (read/flip/set) functions.
  3. Added: The function for calculating the inversion of an invertible matrix by Gaussian elimination method.

(2020/08/01)

  1. Added: Supports for 4-bit matrix operations.
  2. Added: 8to64, 8to128, 16to64, 32to128, 16to128 concatenation functions.

(2020/08/09)

  1. Fixed: Errors of the comments in misc.c.
  2. Added: 4-bit test cases.

(2020/08/10)

  1. Added: Supports for C++.
  2. Added: LowMC Method.

(2020/08/24)

  1. Fixed: Free from C99.

(2020/09/29)

  1. Added: A new matrix transposition function.

(2021/01/12)

  1. Added: Supports for partial 256-bit operations.
  2. Added: Partial 256-bit test cases.

(2021/09/29)

  1. Fixed: An error of printU64/128/256 function.

wbmatrix's People

Contributors

adaptivesca avatar nexus-tyf avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

wbmatrix's Issues

WBSM4

Hi, I just saw your implementation of the white box SM4. Can you tell me which article the white box SM4 is implemented in? Thank you.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.