A lightweight symmetric image encryption cryptosystem in wavelet domain based on an improved sine map

In the era of big data,the number of images transmitted over the public channel increases exponentially.As a result,it is crucial to devise the efficient and highly secure encryption method to safeguard the sensitive image.In this paper,an improved sine map(ISM)possessing a larger chaotic region,more complex chaotic behavior and greater unpredictability is proposed and extensively tested.Drawing upon the strengths of ISM,we introduce a lightweight symmetric image encryption cryptosystem in wavelet domain(WDLIC).The WDLIC employs selective encryption to strike a satisfactory balance between security and speed.Initially,only the low-frequency-low-frequency component is chosen to encrypt utilizing classic permutation and diffusion.Then leveraging the statistical properties in wavelet domain,Gaussianization operation which opens the minds of encrypting image information in wavelet domain is first proposed and employed to all sub-bands.Simulations and theoretical analysis demonstrate the high speed and the remarkable effectiveness of WDLIC.

Performance study of selective encryption in comparison to full encryption for still visual images

Securing digital images is becoming an important concern in today's information security due to the extensive use of secure images that are either transmitted over a network or stored on disks. Image encryption is the most effective way to fulfil confidentiality and protect the privacy of images. Nevertheless, owing to the large size and complex structure of digital images, the computational overhead and processing time needed to carry out full image encryption prove to be limiting factors that inhibit it of being used more heavily in real time. To solve this problem, many recent studies use the selective encryption approach to encrypt significant parts of images with a hope to reduce the encryption overhead. However, it is necessary to realistically evaluate its performance compared to full encryption. In this paper, we study the performance and efficiency of image segmentation methods used in the selective encryption approach, such as edges and face detection methods, in determining the most important parts of visual images. Experiments were performed to analyse the computational results obtained by selective image encryption compared to full image encryption using symmetric encryption algorithms. Experiment results have proven that the selective encryption approach based on edge and face detection can significantly reduce the time of encrypting still visual images as compared to full encryption. Thus, this approach can be considered a good alternative in the implementation of real-time applications that require adequate security levels.

Region of Interest Based Selective Encryption Scheme for Privacy Protection in H.264 Video

A selective encryption scheme for region of interest(ROI) of H.264 video is proposed to protect the personal privacy in a video. The most important part of video can be protected with less cost and operation by only encrypting the content of ROIs. Human face regions are selected as ROI and detected by using Gaussian skin color model. Independent ROI encoding is realized with the mechanism of flexible macro-block ordering(FMO). Frames are divided into grid-like slice-groups which can be combined flexibly to form a required ROI.Both luminance component and chrominance component of the macro-blocks in ROI are modified to achieve good encryption quality and location accuracy. In the process of decryption, the encrypted area is located automatically.There is no need to transmit additional position information of ROIs to the end of decryption. The encrypted video is decrypted correctly with the secret key. JM18.4 software is employed to perform the simulation experiment.Experimental results show the accuracy and effectiveness of our scheme to encrypt and decrypt the ROIs in H.264 video.

Cancellable Multi-Biometric Template Generation Based on Arnold Cat Map and Aliasing

The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric data.This paper presents a cancellable multi-biometric identification scheme that includes four stages:biometric data collection and processing,Arnold’s Cat Map encryption,decimation process to reduce the size,and finalmerging of the four biometrics in a single generated template.First,a 2D matrix of size 128×128 is created based on Arnold’s Cat Map(ACM).The purpose of this rearrangement is to break the correlation between pixels to hide the biometric patterns and merge these patterns together for more security.The decimation is performed to keep the dimensions of the overall cancellable template similar to those of a single template to avoid data redundancy.Moreover,some sort of aliasing occurs due to decimation,contributing to the intended distortion of biometric templates.The hybrid structure that comprises encryption,decimation,andmerging generates encrypted and distorted cancellable templates.The simulation results obtained for performance evaluation show that the system is safe,reliable,and feasible as it achieves high security in the presence of noise.

Application-Aware Client-Side Data Reduction and Encryption of Personal Data in Cloud Backup Services

Cloud backup has been an important issue ever since large quantities of valuable data have been stored on the personal computing devices. Data reduction techniques, such as deduplication, delta encoding, and Lempel-Ziv （LZ） compression, performed at the client side before data transfer can help ease cloud backup by saving network bandwidth and reducing cloud storage space. However, client-side data reduction in cloud backup services faces efficiency and privacy challenges. In this paper, we present Pangolin, a secure and efficient cloud backup service for personal data storage by exploiting application awareness. It can speedup backup operations by application-aware client-side data reduction technique, and mitigate data security risks by integrating selective encryption into data reduction for sensitive applications. Our experimental evaluation, based on a prototype implementation, shows that our scheme can improve data reduction efficiency over the state-of-the-art methods by shortening the backup window size to 33%-75%, and its security mechanism for＇ sensitive applications has negligible impact on backup window size.

Chaos-Based Encryption Algorithm for Compressed Video

Encryption for compressed video streams has attracted increasing attention with the exponential growth of digital multimedia delivery and consumption. However, most algorithms proposed in the literature do not effectively address the peculiarities of security and performance requirements. This paper presents a chaos-based encryption algorithm called the chaotic selective encryption of compressed video (CSECV) which exploits the characteristics of the compressed video. The encryption has three separate layers that can be selected according to the security needs of the application and the processing capability of the client computer. The chaotic pseudo-random sequence generator used to generate the key-sequence to randomize the important fields in the compressed video stream has its parameters encrypted by an asymmetric cipher and placed into the stream. The resulting stream is still a valid video stream. CSECV has significant advantages over existing algorithms for security, decryption speed, implementation flexibility, and error preservation.