Hash Function based on Efficient Chaotic Neural Network

Nabil Abdoun (1, 2) , Safwan El Assad (1) , Mohammad Abu Taha (1) , Rima Assaf (2) , Olivier Deforges (1) , Mohamad Khalil (2)

1 IETR - Institut d'Électronique et des Technologies du numéRique
2 Centre AZM pour la Recherche en Biotechnologie et ses Applications

This paper presents an efficient algorithm for constructing a secure Hash function based on Chaotic Neural Network structure. The proposed Hash function includes two main operations: Generation of Neural Network parameters using fast and efficient Chaotic Generator and Iteration of the message through the Chaotic Neural Network. Our theoretical analysis and experimental simulations showed that the implemented Hash function has good statistical properties, strong Collision Resistance and High Message Sensitivity.

Mots clés: Cryptography; Chaotic map; Neural Network; Hash function

Domaines: Sciences de l'ingénieur [physics]

Nabil Abdoun, Safwan El Assad, Mohammad Abu Taha, Rima Assaf, Olivier Deforges, et al.. Hash Function based on Efficient Chaotic Neural Network. International Conference on Internet Technology and Secured Transactions, Dec 2015, Londres, United Kingdom. pp.32-37, ⟨10.1109/ICITST.2015.7412051⟩. ⟨hal-01250274⟩