On the Cryptanalysis of Two Cryptographic Algorithms That Utilize Chaotic Neural Networks

Ke Qin,B John Oommen

doi:10.1155/2015/468567

Abstract

This paper deals with the security and efficiency issues of two cipher algorithms which utilize the principles of Chaotic Neural Networks (CNNs). The two algorithms that we consider are (1) the CNN-Hash, which is a one-way hash function based on the Piece-Wise Linear Chaotic Map (PWLCM) and the One-Way Coupled Map Lattice (OCML), and (2) the Delayed CNN-Based Encryption (DCBE), which is an encryption algorithm based on the delayed CNN. Although both of these cipher algorithms have their own salient characteristics, our analysis shows that, unfortunately, the CNN-Hash is not secure because it is neither Second-Preimage resistant nor collision resistant. Indeed, one can find a collision with relative ease, demonstrating that its potential as a hash function is flawed. Similarly, we show that the DCBE is also not secure since it is not capable of resisting known plaintext, chosen plaintext, and chosen ciphertext attacks. Furthermore, unfortunately, both schemes are not efficient either, because of the large number of iteration steps involved in their respective implementations.

Highlights

Over the last few decades, the phenomenon of chaos has been widely investigated and applied in a variety of domains including social networks, control systems, and prediction
Our goal is to demonstrate that this cryptography has several weaknesses as follows
The fact that the Delayed CNN-based cryptography still relies on Exclusion OR operations involving strings of length 32 bits renders it more susceptible to statistical attacks

Summary

Introduction

Over the last few decades, the phenomenon of chaos has been widely investigated and applied in a variety of domains including social networks, control systems, and prediction. If a chaotic system starts from a given initial value, different control parameters can yield different output sequences at each iteration. (4) Sensitivity to Initial Values versus Diffusion and Confusion When it concerns a chaotic system, a slightly different initial value may result in a significant difference in the output generated after a sufficiently large number of iterations. As a result of the above observations, chaos has been widely applied in the field of information security since Matthews proposed the first chaotic encryption algorithm [2] in 1984. Kocarev and Tasev presented a public-key encryption [9] and random number generators [10] based on chaotic maps. Most chaos-based ciphers require an excessive number of iterations, without which the ciphertexts are not sensitive to plaintexts.

The CNN-Based Hash Function

The Delayed CNN-Based Cryptography

Findings

Conclusion