Leo Yu Zhang

A chaotic image encryption scheme owning temp-value feedback

Abstract Many round-based chaotic image encryption algorithms employ the permutation–diffusion structure. This structure has been found insecure when the iteration round is equal to one and the secret permutation of some existing schemes can be recovered even a higher round is adopted. In this paper, we present a single round permutation–diffusion chaotic cipher for gray image, in which some temp-value feedback mechanisms are introduced to resist the known attacks. Specifically, we firstly embed the plaintext feedback technique in the permutation process to develop different permutation sequences for different plain-images and then employ plaintext/ciphertext feedback for diffusion to generate equivalent secret key dynamically. Experimental results show that the new scheme owns large key space and can resist the differential attack. It is also efficient.

BREAKING A CHAOTIC IMAGE ENCRYPTION ALGORITHM BASED ON MODULO ADDITION AND XOR OPERATION

This paper re-evaluates the security of a chaotic image encryption algorithm called MCKBA/ HCKBA and finds that it can be broken efficiently with two known plain-images and the corresponding cipher-images. In addition, it is reported that a previously proposed breaking on MCKBA/HCKBA can be further improved by reducing the number of chosen plain-images from four to two. The two attacks are both based on the properties of solving a composite function involving the carry bit, which is composed of the modulo addition and the bitwise OR operations. Both rigorous theoretical analysis and detailed experimental results are provided.

Cryptanalyzing a chaos-based image encryption algorithm using alternate structure

Recently, a chaos-based image encryption algorithm with an alternate structure (IEAS) was proposed. This paper applies the differential cryptanalysis on the IEAS and finds that some of its properties favor the differential attack which can recover an equivalent secret key with only a few number of chosen plain-images. Detailed procedures for cryptanalyzing IEAS with a lower round number are presented. Both theoretical analysis and experimental results are provided to show the vulnerability of IEAS against differential attack. In addition, some other security defects of IEAS, including insensitivity with respect to changes of plain-images and insufficient size of the key space, are also pointed out and verified.

Embedding cryptographic features in compressive sensing

Compressive sensing (CS) has been widely studied and applied in many fields. Recently, the way to perform secure compressive sensing (SCS) has become a topic of growing interest. The existing works on SCS usually take the sensing matrix as a key and can only be considered as preliminary explorations on SCS. In this paper, we firstly propose some possible encryption models for CS. It is believed that these models will provide a new point of view and stimulate further research in both CS and cryptography. Then, we demonstrate that random permutation is an acceptable permutation with overwhelming probability, which can effectively relax the Restricted Isometry Constant for parallel compressive sensing. Moreover, random permutation is utilized to design a secure parallel compressive sensing scheme. Security analysis indicates that the proposed scheme can achieve the asymptotic spherical secrecy. Meanwhile, the realization of chaos is used to validate the feasibility of one of the proposed encryption models for CS. Lastly, results verify that the embedding random permutation based encryption enhances the compression performance and the scheme possesses high transmission robustness against additive white Gaussian noise and cropping attack.

Bi-level Protected Compressive Sampling

There have been some pioneering works concerning embedding cryptographic properties in Compressive Sampling (CS) but it turns out that the concise linear projection encoding process makes this approach ineffective. Here we introduce a bi-level protection (BLP) model for constructing secure compressive sampling scheme. Then we propose several techniques to establish secret key-related sparsifying basis and deploy them into our new CS model. It is demonstrated that the encoding process is simply a random linear projection, which is the same as the traditional model. However, decoding the measurements requires the knowledge of both the key-related sensing matrix and the key-related sparsifying basis. We apply the proposed model to construct digital image cipher under the parallel compressive sampling reconstruction framework. The main properties of this cipher, such as low computational complexity, compressibility, robustness and computational secrecy under known/chosen plaintext attacks, are thoroughly studied. It is shown that compressive sampling scheme based on our BLP model is robust under various attack scenarios although the encoding process is a simple linear projection.Some pioneering works have investigated embedding cryptographic properties in compressive sampling (CS) in a way similar to one-time pad symmetric cipher. This paper tackles the problem of constructing a CS-based symmetric cipher under the key reuse circumstance, i.e., the cipher is resistant to common attacks even when a fixed measurement matrix is used multiple times. To this end, we suggest a bi-level protected CS (BLP-CS) model which makes use of the advantage of measurement matrix construction without restricted isometry property (RIP). Specifically, two kinds of artificial basis mismatch techniques are investigated to construct key-related sparsifying bases. It is demonstrated that the encoding process of BLP-CS is simply a random linear projection, which is the same as the basic CS model. However, decoding the linear measurements requires knowledge of both the key-dependent sensing matrix and its sparsifying basis. The proposed model is exemplified by sampling images as a joint data acquisition and protection layer for resource-limited wireless sensors. Simulation results and numerical analyses have justified that the new model can be applied in circumstances where the measurement matrix can be reused.

Cryptanalyzing a class of image encryption schemes based on Chinese remainder theorem

Abstract As a fundamental theorem in number theory, the Chinese Reminder Theorem (CRT) is widely used to construct cryptographic primitives. This paper investigates the security of a class of image encryption schemes based on CRT, referred to as CECRT. Making use of some properties of CRT, the equivalent secret key of CECRT can be recovered efficiently. The required number of pairs of chosen plaintext and the corresponding ciphertext is only ( 1 + ⌈ ( log 2 L ) / l ⌉ ) , the attack complexity is only O ( L ), where L is the plaintext length and l is the number of bits representing a plaintext symbol. In addition, other defects of CECRT, such as invalid compression function and low sensitivity to plaintext, are reported. The work in this paper will help clarify positive role of CRT in cryptology.

On the Security of a Class of Diffusion Mechanisms for Image Encryption

The need for fast and strong image cryptosystems motivates researchers to develop new techniques to apply traditional cryptographic primitives in order to exploit the intrinsic features of digital images. One of the most popular and mature technique is the use of complex dynamic phenomena, including chaotic orbits and quantum walks, to generate the required key stream. In this paper, under the assumption of plaintext attacks we investigate the security of a classic diffusion mechanism (and of its variants) used as the core cryptographic primitive in some image cryptosystems based on the aforementioned complex dynamic phenomena. We have theoretically found that regardless of the key schedule process, the data complexity for recovering each element of the equivalent secret key from these diffusion mechanisms is only

Joint quantization and diffusion for compressed sensing measurements of natural images

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Robust coding of encrypted images via structural matrix

(1). The proposed analysis is validated by means of numerical examples. Some additional cryptographic applications of this paper are also discussed.

Security Analysis of Some Diffusion Mechanisms Used in Chaotic Ciphers

Recent research advances have revealed the computational secrecy of the compressed sensing (CS) paradigm. Perfect secrecy can also be achieved by normalizing the CS measurement vector. However, these findings are established on real-valued measurements while digital devices can only store the samples at a finite precision. Based on the distribution of measurements of natural images sensed by structurally random ensemble, a joint quantization and diffusion approach for the real-valued measurements is suggested. In this way, a nonlinear cryptographic diffusion is intrinsically imposed on the CS quantization process and the overall security level is thus enhanced. It is shown that the proposed scheme is able to resist known-plaintext attack while the original CS scheme without quantization cannot.