ranea / CASCADA

A tool to evaluate the security of cryptographic primitives against distinguishing attacks with bit-vector SMT solvers.

CASCADA

CASCADA (Characteristic Automated Search of Cryptographic Algorithms for Distinguishing Attacks) is a Python 3 library to evaluate the security of cryptographic primitives, specially block ciphers, against distinguishing attacks with bit-vector SMT solvers.

A detailed introduction of CASCADA can be found in the paper Characteristic Automated Search of Cryptographic Algorithms for Distinguishing Attacks (CASCADA).

CASCADA implements several SMT-based automated search methods to search for characteristics and zero-probability properties to evaluate the security of ciphers against:

• differential cryptanalysis
• related-key differential cryptanalysis
• rotational-XOR cryptanalysis
• impossible-differential cryptanalysis
• related-key impossible-differential cryptanalysis
• impossible-rotational-XOR cryptanalysis
• linear cryptanalysis
• zero-correlation cryptanalysis

The online documentation of CASCADA can be found here.

Installation

CASCADA requires Python 3 (>= 3.10) and the following Python libraries:

• cython
• sympy
• bidict
• cffi
• wurlitzer
• pySMT

These libraries can be easily installed with pip:

pip install cython sympy bidict cffi wurlitzer pysmt

CASCADA also requires an SMT solver supporting the bit-vector theory, installed through pySMT. For example, the SMT solver boolector can be installed through pySMT by :

pysmt-install --btor

Optionally, hypothesis can be installed to run the tests, and sphinx and sphinx-rtd-theme to build the documentation.

Citation

If you use CASCADA, please consider citing the paper:

@article{DBLP:journals/iet-ifs/RaneaR22,
  author     = {Adri{\'{a}}n Ranea and Vincent Rijmen},
  title      = {Characteristic automated search of cryptographic algorithms
                for distinguishing attacks ({CASCADA})},
  journal    = {{IET} Inf. Secur.},
  volume     = {16},
  number     = {6},
  pages      = {470--481},
  year       = {2022},
  doi        = {https://doi.org/10.1049/ise2.12077}
}