Puzzle -A Novel Video Encryption Algorithm

Abstract. Networked multimedia applications have matured in recent years to be deployed in a larger scale in the Internet. Confidentiality is one of the primary concerns of these services for their commercial usages, e.g. in video on demand services or in video conferences. In particular, video encryption algorithms are strongly required that fulfill real-time requirements. In this paper we present the video encryption algorithm Puzzle to encrypting video streams in software. It is fast enough to fulfill real-time constraints and to provide a sufficient security. Puzzle is a video compression independent algorithm which can be easily incorporated into existing multimedia systems

A Novel Latin Square Image Cipher

In this paper, we introduce a symmetric-key Latin square image cipher (LSIC) for grayscale and color images. Our contributions to the image encryption community include 1) we develop new Latin square image encryption primitives including Latin Square Whitening, Latin Square S-box and Latin Square P-box ; 2) we provide a new way of integrating probabilistic encryption in image encryption by embedding random noise in the least significant image bit-plane; and 3) we construct LSIC with these Latin square image encryption primitives all on one keyed Latin square in a new loom-like substitution-permutation network. Consequently, the proposed LSIC achieve many desired properties of a secure cipher including a large key space, high key sensitivities, uniformly distributed ciphertext, excellent confusion and diffusion properties, semantically secure, and robustness against channel noise. Theoretical analysis show that the LSIC has good resistance to many attack models including brute-force attacks, ciphertext-only attacks, known-plaintext attacks and chosen-plaintext attacks. Experimental analysis under extensive simulation results using the complete USC-SIPI Miscellaneous image dataset demonstrate that LSIC outperforms or reach state of the art suggested by many peer algorithms. All these analysis and results demonstrate that the LSIC is very suitable for digital image encryption. Finally, we open source the LSIC MATLAB code under webpage https://sites.google.com/site/tuftsyuewu/source-code.Comment: 26 pages, 17 figures, and 7 table

A review and open issues of multifarious image steganography techniques in spatial domain

Nowadays, information hiding is becoming a helpful technique and fetch more attention due fast growth of using internet, it is applied for sending secret information by using different techniques. Steganography is one of major important technique in information hiding. Steganography is science of concealing the secure information within a carrier object to provide the secure communication though the internet, so that no one can recognize and detect it’s except the sender & receiver. In steganography, many various carrier formats can be used such as an image, video, protocol, audio. The digital image is most popular used as a carrier file due its frequency on internet. There are many techniques variable for image steganography, each has own strong and weak points. In this study, we conducted a review of image steganography in spatial domain to explore the term image steganography by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2014 to 2017. The aims of this review is provides an overview of image steganography and comparison between approved studies are discussed according to the pixel selection, payload capacity and embedding algorithm to open important research issues in the future works and obtain a robust method

Hungarian-Puzzled Text with Dynamic Quadratic Embedding Steganography

Least-Significant-Bit (LSB) is one of the popular and frequently used steganography techniques to hide a secret message in a digital medium. Its popularity is due to its simplicity in implementation and ease of use. However, such simplicity comes with vulnerabilities. An embedded secret message using the traditional LSB insertion is easily decodable when the stego image is suspected to be hiding a secret message.  In this paper, we propose a novel secure and high quality LSB embedding technique. The security of the embedded payload is employed through introducing a novel quadratic embedding sequence. The embedding technique is also text dependent and has non-bounded inputs, making the possibilities of decoding infinite. Due to the exponential growth of and quadratic embedding, a novel cyclic technique is also introduced for the sequence that goes beyond the limits of the cover medium. The proposed method also aims to reduce the noise arising from embedding the secret message by reducing bits changed. This is done by partitioning the cover medium and the secret message into N partitions and artificially creating an assignment problem based on bit change criteria. The assignment problem will be solved using the Hungarian algorithm that will puzzle the secret message partition for an overall least bit change

Security and Privacy Issues of Big Data

This chapter revises the most important aspects in how computing infrastructures should be configured and intelligently managed to fulfill the most notably security aspects required by Big Data applications. One of them is privacy. It is a pertinent aspect to be addressed because users share more and more personal data and content through their devices and computers to social networks and public clouds. So, a secure framework to social networks is a very hot topic research. This last topic is addressed in one of the two sections of the current chapter with case studies. In addition, the traditional mechanisms to support security such as firewalls and demilitarized zones are not suitable to be applied in computing systems to support Big Data. SDN is an emergent management solution that could become a convenient mechanism to implement security in Big Data systems, as we show through a second case study at the end of the chapter. This also discusses current relevant work and identifies open issues.Comment: In book Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, IGI Global, 201