21 research outputs found

    A novel secure H.264 transcoder using selective encryption

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    Transparent encryption with scalable video communication: Lower-latency, CABAC-based schemes

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    Selective encryption masks all of the content without completely hiding it, as full encryption would do at a cost in encryption delay and increased bandwidth. Many commercial applications of video encryption do not even require selective encryption, because greater utility can be gained from transparent encryption, i.e. allowing prospective viewers to glimpse a reduced quality version of the content as a taster. Our lightweight selective encryption scheme when applied to scalable video coding is well suited to transparent encryption. The paper illustrates the gains in reducing delay and increased distortion arising from a transparent encryption that leaves reduced quality base layer in the clear. Reduced encryption of B-frames is a further step beyond transparent encryption in which the computational overhead reduction is traded against content security and limited distortion. This spectrum of video encryption possibilities is analyzed in this paper, though all of the schemes maintain decoder compatibility and add no bitrate overhead as a result of jointly encoding and encrypting the input video by virtue of carefully selecting the entropy coding parameters that are encrypted. The schemes are suitable both for H.264 and HEVC codecs, though demonstrated in the paper for H.264. Selected Content Adaptive Binary Arithmetic Coding (CABAC) parameters are encrypted by a lightweight Exclusive OR technique, which is chosen for practicality

    End-to-end security for video distribution

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    SLEPX: An Efficient Lightweight Cipher for Visual Protection of Scalable HEVC Extension

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    This paper proposes a lightweight cipher scheme aimed at the scalable extension of the High Efficiency Video Coding (HEVC) codec, referred to as the Scalable HEVC (SHVC) standard. This stream cipher, Symmetric Cipher for Lightweight Encryption based on Permutation and EXlusive OR (SLEPX), applies Selective Encryption (SE) over suitable coding syntax elements in the SHVC layers. This is achieved minimal computational complexity and delay. The algorithm also conserves most SHVC functionalities, i.e. preservation of bit-length, decoder format-compliance, and error resilience. For comparative analysis, results were taken and compared with other state-of-art ciphers i.e. Exclusive-OR (XOR) and the Advanced Encryption Standard (AES). The performance of SLEPX is also compared with existing video SE solutions to confirm the efficiency of the adopted scheme. The experimental results demonstrate that SLEPX is as secure as AES in terms of visual protection, while computationally efficient comparable with a basic XOR cipher. Visual quality assessment, security analysis and extensive cryptanalysis (based on numerical values of selected binstrings) also showed the effectiveness of SLEPX’s visual protection scheme for SHVC compared to previously-employed cryptographic technique

    Privacy-Friendly Photo Sharing and Relevant Applications Beyond

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    Popularization of online photo sharing brings people great convenience, but has also raised concerns for privacy. Researchers proposed various approaches to enable image privacy, most of which focus on encrypting or distorting image visual content. In this thesis, we investigate novel solutions to protect image privacy with a particular emphasis on online photo sharing. To this end, we propose not only algorithms to protect visual privacy in image content but also design of architectures for privacy-preserving photo sharing. Beyond privacy, we also explore additional impacts and potentials of employing daily images in other three relevant applications. First, we propose and study two image encoding algorithms to protect visual content in image, within a Secure JPEG framework. The first method scrambles a JPEG image by randomly changing the signs of its DCT coefficients based on a secret key. The second method, named JPEG Transmorphing, allows one to protect arbitrary image regions with any obfuscation, while secretly preserving the original image regions in application segments of the obfuscated JPEG image. Performance evaluations reveal a good degree of storage overhead and privacy protection capability for both methods, and particularly a good level of pleasantness for JPEG Transmorphing, if proper manipulations are applied. Second, we investigate the design of two architectures for privacy-preserving photo sharing. The first architecture, named ProShare, is built on a public key infrastructure (PKI) integrated with a ciphertext-policy attribute-based encryption (CP-ABE), to enable the secure and efficient access to user-posted photos protected by Secure JPEG. The second architecture is named ProShare S, in which a photo sharing service provider helps users make photo sharing decisions automatically based on their past decisions using machine learning. The photo sharing service analyzes not only the content of a user's photo, but also context information about the image capture and a prospective requester, and finally makes decision whether or not to share a particular photo to the requester, and if yes, at which granularity. A user study along with extensive evaluations were performed to validate the proposed architecture. In the end, we research into three relevant topics in regard to daily photos captured or shared by people, but beyond their privacy implications. In the first study, inspired by JPEG Transmorphing, we propose an animated JPEG file format, named aJPEG. aJPEG preserves its animation frames as application markers in a JPEG image and provides smaller file size and better image quality than conventional GIF. In the second study, we attempt to understand the impact of popular image manipulations applied in online photo sharing on evoked emotions of observers. The study reveals that image manipulations indeed influence people's emotion, but such impact also depends on the image content. In the last study, we employ a deep convolutional neural network (CNN), the GoogLeNet model, to perform automatic food image detection and categorization. The promising results obtained provide meaningful insights in design of automatic dietary assessment system based on multimedia techniques, e.g. image analysis

    System Steganalysis: Implementation Vulnerabilities and Side-Channel Attacks Against Digital Steganography Systems

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    Steganography is the process of hiding information in plain sight, it is a technology that can be used to hide data and facilitate secret communications. Steganography is commonly seen in the digital domain where the pervasive nature of media content (image, audio, video) provides an ideal avenue for hiding secret information. In recent years, video steganography has shown to be a highly suitable alternative to image and audio steganography due to its potential advantages (capacity, flexibility, popularity). An increased interest towards research in video steganography has led to the development of video stego-systems that are now available to the public. Many of these stego-systems have not yet been subjected to analysis or evaluation, and their capabilities for performing secure, practical, and effective video steganography are unknown. This thesis presents a comprehensive analysis of the state-of-the-art in practical video steganography. Video-based stego-systems are identified and examined using steganalytic techniques (system steganalysis) to determine the security practices of relevant stego-systems. The research in this thesis is conducted through a series of case studies that aim to provide novel insights in the field of steganalysis and its capabilities towards practical video steganography. The results of this work demonstrate the impact of system attacks over the practical state-of-the-art in video steganography. Through this research, it is evident that video-based stego-systems are highly vulnerable and fail to follow many of the well-understood security practices in the field. Consequently, it is possible to confidently detect each stego-system with a high rate of accuracy. As a result of this research, it is clear that current work in practical video steganography demonstrates a failure to address key principles and best practices in the field. Continued efforts to address this will provide safe and secure steganographic technologies

    Service-oriented models for audiovisual content storage

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    What are the important topics to understand if involved with storage services to hold digital audiovisual content? This report takes a look at how content is created and moves into and out of storage; the storage service value networks and architectures found now and expected in the future; what sort of data transfer is expected to and from an audiovisual archive; what transfer protocols to use; and a summary of security and interface issues
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