# Cryptanalysis of a New Color Image Encryption Using Combination of the 1D Chaotic Map
## 1 Introduction  
Encryption of color image is a critical issue for confidentiality and security. Lots of encryption methods [1; 2; 3; 4; 5; 6; 7; 8] using chaotic maps have been proposed for the excellent properties such as ergodicity and sensitivity to initial condition and control parameters. However, some cryptanalysis articles in [9; 10; 11; 12; 13; 14] have verified the vulnerability of common chaotic encryption methods based on the permutation-diffusion structure. Hence, chaotic image encryption algorithms [15; 16], combined with other special technologies, such as DNA, information entropy etc., have been nearly introduced. For example, the sensitivity mechanism is built up utilizing the information entropy of the plain-image in [16]. Cryptanalysis works have been correspondingly proposed in [17; 18] to evaluate the security of image cryptosystems, which can improve the security of the existing cryptosystems. For example, [PERSON] et al. attacked the chaotic image encryption algorithm based on information entropy in [18].  
Recently, some more chaotic image encryption algorithms based on Latin square have been designed [19; 20; 21] due to the cryptography property of Latin square. But [PERSON] et al., found out an algebraic weakness in [22] and the chaotic image cipher is broken by chosen-plaintext attack with chosen ciphertext attack. In addition, [PERSON] et al. in [23] found out the defect of the feedback image encryption algorithm with compound chaotic stream cipher based on perturbation and attacked the algorithm.  
In [24], the image block encryption algorithm achieves high security level where three different chaotic maps are utilized respectively for controlling pixel shuffling, blocking size, and value encryption. However, [PERSON] found out that there are some critical security defects in [25] and derive the secret key with a chosen plaintext attack.  
Most cryptanalysis works have mainly focused on single round of permutation-diffusion image ciphers. However, most encryption schemes are based on multiple rounds of permutation-diffusion [26; 27; 28; 29; 30; 31; 32]. In [29], two rounds of permutation and pixel adaptive diffusion was proposed. In [32], an improved chaotic image encryption method using Latin square based on two rounds of permutation-diffusionwas proposed, which has weak security defects. However, [PERSON] et al. find out the equivalent key streams and attacked the scheme in [33] and attacked the scheme.  
However, most chaotic maps, used in generating the security key in encryption process, are multi-dimensional, which cause high level computation complexity. Recently, some 1D chaotic map encryption algorithms have been proposed in [34; 35; 36] which have lower computation complexity for software/hardware implementations. In [37] a new 1D chaotic map model is proposed where a new 1D chaotic map is made by using the classic chaotic map such as logistic, sine and Chebyshev maps. A bifurcation property of the chaotic map and the Lyapunov exponent, in addition to information entropy evaluation are much better than the classic chaotic system.  
Aiming at [37], [PERSON] et al., found out an algebraic weakness of the cryptosystem in [38] and attacked its equivalent cryptographic scheme by chosen plaintext attack. The authors acquire the rotation factor by constructing two special functions and attack permutation with the methods in [39; 40] which have high computation complexity. In this paper, a novel attack method to directly crack the original encryption scheme in [37] is proposed. The proposed method attacks the factor and diffusion using the properties of bit-level Xor and attacks permutation with a new scheme which has lower computation.  
This paper organizes as follows. Section 2 overviews the new encryption method. Security of the scheme is analyzed and the attack scheme by chosen plaintext images is presented in Section 3. The simulation experiments to verify the proposed method are presented in Section 4. Conclusions are provided in Section 5.