Image encryption: Generating visually meaningful encrypted images
Introduction
In the past ten years, “Cloud” has become a popular keyword in the computer society. To overcome the limitations in the storage and computation capability of a single computer, cloud computing technology provides individuals and organizations a sufficiently large online space to store multimedia data (e.g. documents, videos and images), and offers people a convenient way to access and share data over the network. Due to the fact that these multimedia data may contain private, valued or even classified information, preventing these important information from leakage becomes an important and urgent issue for individuals and organizations [33], [34]. Image encryption is an efficient tool to provide security to these multimedia data.
Many image encryption algorithms have been proposed to protect images by changing their pixel values and/or locations using different technologies [5], [19], [35]. They can be classified into the frequency-domain and spatial-domain image encryption algorithms. Using security key coefficients, the frequency-domain image encryption algorithms are designed to change image data in the frequency domain or alter the transform function, such as the discrete fractional Fourier transform [18], [21], [26], quantum Fourier transform [31] and reciprocal-orthogonal parametric transform [6]. The spatial-domain image encryption algorithms are based on the famous Substitution-Permutation Network (SPN) that utilizes a substitution process to change image pixel values and a permutation process to change image pixel positions. These permutation and substitution processes are based on different technologies including the advanced encryption standard (AES) [24], P-Fibonacci transform [40], wave transmission [20], elliptic curve ElGamal [8], gray code [36], random grids [10], Latin squares [30] and chaotic systems [9], [17], [38], [41]. Both the spatial-domain and frequency-domain image encryption algorithms are able to protect images with a high level of security [27], [39]. Their output encrypted images are all visually texture-like or noise-like, such as images in Fig. 1(a) and (b). However, since the formats of these encrypted images are limited to noise-like and texture-like, it is easy to distinguish them from normal visually meaningful images. From the security point of view, this texture-like or noise-like feature is an obvious visual sign indicating the presence of an encrypted image [37] that may contain important information. As a result, an encrypted image with similar features as noise-like or texture-like definitely brings increasing people’s attentions and thus leads to a large number of attacks and analysis. These include different types of cryptanalysis, illegal edition, modification or even deletion of image contents. All these increase the possibility of information leakage, loss or modification.
To address these problems, in this paper, we propose a new concept of image encryption to transform original images into visually meaningful encrypted images, such as images in Fig. 1(c). This is because people generally consider these images as normal images rather than encrypted ones. Based on this concept, we introduce an image encryption system. It not only protects images in a normal way that most existing encryption methods do, but also provides an additional visual protection. Simulation results and security analysis are provided.
Section snippets
New concept of image encryption
Most existing image encryption algorithms protect original images by transforming them into texture-like or noise-like encrypted images with a nearly uniform distribution of pixel values. As a result, the encrypted images can withstand different types of attacks, protecting original image information with a high level of security. However, this texture-like or noise-like feature is an obvious visual sign of encrypted images. It definitely catches more people’s attentions and thus brings a
New image encryption system
The key issue of the proposed concept is how to generate VMEIs. Motivated by technologies of image hiding and watermarking, this section introduces a new image encryption system (NIES) as an implementation example of the proposed concept.
Simulation results and performance analysis
This section provides several simulation examples and performance analysis to show the NIES’s encryption performance. In this paper, all reference images are four times larger than the original images to be encrypted.
Security analysis
Generally speaking, the security of an encryption algorithm mainly depends on its security key design [23]. The proposed NIES has a sufficiently large key space and high key sensitivity.
Conclusions
To address the security weakness of most existing encryption algorithms whose texture-like or noise-like encrypted images may bring a large number of attacks and analysis, this paper has introduced a new concept of image encryption to generate visually meaningful encrypted images that usually are considered as normal images rather than encrypted ones. With a large amount of formats of encrypted images, the proposed concept ensures the attackers’ difficulty of correctly distinguishing and
Acknowledgment
This work was supported in part by the Macau Science and Technology Development Fund under grant FDCT/017/2012/A1 and by the Research Committee at University of Macau under grants MYRG2014-00003-FST, MRG017/ZYC/2014/FST, MYRG113(Y1-L3)-FST12-ZYC and MRG001/ZYC/2013/FST.
References (41)
- et al.
Robust lossless data hiding using clustering and statistical quantity histogram
Neurocomputing
(2012) - et al.
Content-adaptive reliable robust lossless data embedding
Neurocomputing
(2012) - et al.
Discrete fractional wavelet transform and its application to multiple encryption
Inf. Sci.
(2013) - et al.
Wavelet transforms that map integers to integers
Appl. Comput. Harmonic Anal.
(1998) - et al.
Personalized information encryption using ECG signals with chaotic functions
Inf. Sci.
(2012) - et al.
A symmetric image encryption scheme based on 3D chaotic cat maps
Chaos, Solitons & Fractals
(2004) - et al.
Multi-image encryption by circular random grids
Inf. Sci.
(2012) - et al.
A local Tchebichef moments-based robust image watermarking
Signal Process.
(2009) - et al.
Reversibility improved lossless data hiding
Signal Process.
(2009) - et al.
Geometric distortion insensitive image watermarking in affine covariant regions
IEEE Trans. Syst. Man Cybern. Part C: Appl. Rev.
(2010)
An image encryption scheme based on irregularly decimated chaotic maps
Signal Process.: Image Commun.
Optical double image encryption employing a pseudo image technique in the Fourier domain
Opt. Commun.
2d sine logistic modulation map for image encryption
Inf. Sci.
A novel image encryption algorithm based on self-adaptive wave transmission
Signal Process.
Image encryption based on the fractional Fourier transform over finite fields
Signal Process.
Double image encryption based on discrete multiple-parameter fractional Fourier transform and chaotic maps
Opt. Commun.
Image cryptographic algorithm based on the haar wavelet transform
Information Sciences
Quantum cryptographic algorithm for color images using quantum Fourier transform and double random-phase encoding
Information Sciences
Gray code permutation algorithm for high-dimensional data encryption
Information Sciences
Designing an efficient image encryption-then-compression system via prediction error clustering and random permutation
IEEE Transactions on Information Forensics and Security
Cited by (195)
3D mesh encryption with differentiated visual effect and high efficiency based on chaotic system
2024, Expert Systems with ApplicationsMultiple face images encryption based on a new non-adjacent dynamic coupled mapping lattice
2024, Expert Systems with ApplicationsImage transformation based on optical reservoir computing for image security
2024, Expert Systems with ApplicationsImage hiding using invertible neural network and similarity of bits pairs
2024, Applied Soft ComputingVisually meaningful image encryption based on 2D compressive sensing and dynamic embedding
2023, Journal of Information Security and Applications