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

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

Algorithms and Architectures for Secure Embedded Multimedia Systems

Embedded multimedia systems provide real-time video support for applications in entertainment (mobile phones, internet video websites), defense (video-surveillance and tracking) and public-domain (tele-medicine, remote and distant learning, traffic monitoring and management). With the widespread deployment of such real-time embedded systems, there has been an increasing concern over the security and authentication of concerned multimedia data. While several (software) algorithms and hardware architectures have been proposed in the research literature to support multimedia security, these fail to address embedded applications whose performance specifications have tighter constraints on computational power and available hardware resources. The goals of this dissertation research are two fold: 1. To develop novel algorithms for joint video compression and encryption. The proposed algorithms reduce the computational requirements of multimedia encryption algorithms. We propose an approach that uses the compression parameters instead of compressed bitstream for video encryption. 2. Hardware acceleration of proposed algorithms over reconfigurable computing platforms such as FPGA and over VLSI circuits. We use signal processing knowledge to make the algorithms suitable for hardware optimizations and try to reduce the critical path of circuits using hardware-specific optimizations. The proposed algorithms ensures a considerable level of security for low-power embedded systems such as portable video players and surveillance cameras. These schemes have zero or little compression losses and preserve the desired properties of compressed bitstream in encrypted bitstream to ensure secure and scalable transmission of videos over heterogeneous networks. They also support indexing, search and retrieval in secure multimedia digital libraries. This property is crucial not only for police and armed forces to retrieve information about a suspect from a large video database of surveillance feeds, but extremely helpful for data centers (such as those used by youtube, aol and metacafe) in reducing the computation cost in search and retrieval of desired videos

Multimedia

The nowadays ubiquitous and effortless digital data capture and processing capabilities offered by the majority of devices, lead to an unprecedented penetration of multimedia content in our everyday life. To make the most of this phenomenon, the rapidly increasing volume and usage of digitised content requires constant re-evaluation and adaptation of multimedia methodologies, in order to meet the relentless change of requirements from both the user and system perspectives. Advances in Multimedia provides readers with an overview of the ever-growing field of multimedia by bringing together various research studies and surveys from different subfields that point out such important aspects. Some of the main topics that this book deals with include: multimedia management in peer-to-peer structures & wireless networks, security characteristics in multimedia, semantic gap bridging for multimedia content and novel multimedia applications

Efficient simultaneous encryption and compression of digital videos in computationally constrained applications

This thesis is concerned with the secure video transmission over open and wireless network channels. This would facilitate adequate interaction in computationally constrained applications among trusted entities such as in disaster/conflict zones, secure airborne transmission of videos for intelligence/security or surveillance purposes, and secure video communication for law enforcing agencies in crime fighting or in proactive forensics. Video content is generally too large and vulnerable to eavesdropping when transmitted over open network channels so that compression and encryption become very essential for storage and/or transmission. In terms of security, wireless channels, are more vulnerable than other kinds of mediums to a variety of attacks and eavesdropping. Since wireless communication is the main mode in the above applications, protecting video transmissions from unauthorized access through such network channels is a must. The main and multi-faceted challenges that one faces in implementing such a task are related to competing, and to some extent conflicting, requirements of a number of standard control factors relating to the constrained bandwidth, reasonably high image quality at the receiving end, the execution time, and robustness against security attacks. Applying both compression and encryption techniques simultaneously is a very tough challenge due to the fact that we need to optimize the compression ratio, time complexity, security and the quality simultaneously. There are different available image/video compression schemes that provide reasonable compression while attempting to maintain image quality, such as JPEG, MPEG and JPEG2000. The main approach to video compression is based on detecting and removing spatial correlation within the video frames as well as temporal correlations across the video frames. Temporal correlations are expected to be more evident across sequences of frames captured within a short period of time (often a fraction of a second). Correlation can be measured in terms of similarity between blocks of pixels. Frequency domain transforms such as the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT) have both been used restructure the frequency content (coefficients) to become amenable for efficient detection. JPEG and MPEG use DCT while JPEG2000 uses DWT. Removing spatial/temporal correlation encodes only one block from each class of equivalent (i.e. similar) blocks and remembering the position of all other block within the equivalence class. JPEG2000 compressed images achieve higher image quality than JPEG for the same compression ratios, while DCT based coding suffer from noticeable distortion at high compression ratio but when applied to any block it is easy to isolate the significant coefficients from the non-significant ones. Efficient video encryption in computationally constrained applications is another challenge on its own. It has long been recognised that selective encryption is the only viable approach to deal with the overwhelming file size. Selection can be made in the spatial or frequency domain. Efficiency of simultaneous compression and encryption is a good reason for us to apply selective encryption in the frequency domain. In this thesis we develop a hybrid of DWT and DCT for improved image/video compression in terms of image quality, compression ratio, bandwidth, and efficiency. We shall also investigate other techniques that have similar properties to the DCT in terms of representation of significant wavelet coefficients. The statistical properties of wavelet transform high frequency sub-bands provide one such approach, and we also propose phase sensing as another alternative but very efficient scheme. Simultaneous compression and encryption, in our investigations, were aimed at finding the best way of applying these two tasks in parallel by selecting some wavelet sub-bands for encryptions and applying compression on the other sub-bands. Since most spatial/temporal correlation appear in the high frequency wavelet sub-bands and the LL sub-bands of wavelet transformed images approximate the original images then we select the LL-sub-band data for encryption and the non-LL high frequency sub-band coefficients for compression. We also follow the common practice of using stream ciphers to meet efficiency requirements of real-time transmission. For key stream generation we investigated a number of schemes and the ultimate choice will depend on robustness to attacks. The still image (i.e. RF’s) are compressed with a modified EZW wavelet scheme by applying the DCT on the blocks of the wavelet sub-bands, selecting appropriate thresholds for determining significance of coefficients, and encrypting the EZW thresholds only with a simple 10-bit LFSR cipher This scheme is reasonably efficient in terms of processing time, compression ratio, image quality, as well was security robustness against statistical and frequency attack. However, many areas for improvements were identified as necessary to achieve the objectives of the thesis. Through a process of refinement we developed and tested 3 different secure efficient video compression schemes, whereby at each step we improve the performance of the scheme in the previous step. Extensive experiments are conducted to test performance of the new scheme, at each refined stage, in terms of efficiency, compression ratio, image quality, and security robustness. Depending on the aspects of compression that needs improvement at each refinement step, we replaced the previous block coding scheme with a more appropriate one from among the 3 above mentioned schemes (i.e. DCT, Edge sensing and phase sensing) for the reference frames or the non-reference ones. In subsequent refinement steps we apply encryption to a slightly expanded LL-sub-band using successively more secure stream ciphers, but with different approaches to key stream generation. In the first refinement step, encryption utilized two LFSRs seeded with three secret keys to scramble the significant wavelet LL-coefficients multiple times. In the second approach, the encryption algorithm utilises LFSR to scramble the wavelet coefficients of the edges extracted from the low frequency sub-band. These edges are mapped from the high frequency sub-bands using different threshold. Finally, use a version of the A5 cipher combined with chaotic logistic map to encrypt the significant parameters of the LL sub-band. Our empirical results show that the refinement process achieves the ultimate objectives of the thesis, i.e. efficient secure video compression scheme that is scalable in terms of the frame size at about 100 fps and satisfying the following features; high compression, reasonable quality, and resistance to the statistical, frequency and the brute force attack with low computational processing. Although image quality fluctuates depending on video complexity, in the conclusion we recommend an adaptive implementation of our scheme. Although this thesis does not deal with transmission tasks but the efficiency achieved in terms of video encryption and compression time as well as in compression ratios will be sufficient for real-time secure transmission of video using commercially available mobile computing devices

Research on digital image watermark encryption based on hyperchaos

The digital watermarking technique embeds meaningful information into one or more watermark images hidden in one image, in which it is known as a secret carrier. It is difficult for a hacker to extract or remove any hidden watermark from an image, and especially to crack so called digital watermark. The combination of digital watermarking technique and traditional image encryption technique is able to greatly improve anti-hacking capability, which suggests it is a good method for keeping the integrity of the original image. The research works contained in this thesis include: (1)A literature review the hyperchaotic watermarking technique is relatively more advantageous, and becomes the main subject in this programme. (2)The theoretical foundation of watermarking technologies, including the human visual system (HVS), the colour space transform, discrete wavelet transform (DWT), the main watermark embedding algorithms, and the mainstream methods for improving watermark robustness and for evaluating watermark embedding performance. (3) The devised hyperchaotic scrambling technique it has been applied to colour image watermark that helps to improve the image encryption and anti-cracking capabilities. The experiments in this research prove the robustness and some other advantages of the invented technique. This thesis focuses on combining the chaotic scrambling and wavelet watermark embedding to achieve a hyperchaotic digital watermark to encrypt digital products, with the human visual system (HVS) and other factors taken into account. This research is of significant importance and has industrial application value

SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search

The $k$-Nearest Neighbor Search ($k$-NNS) is the backbone of several cloud-based services such as recommender systems, face recognition, and database search on text and images. In these services, the client sends the query to the cloud server and receives the response in which case the query and response are revealed to the service provider. Such data disclosures are unacceptable in several scenarios due to the sensitivity of data and/or privacy laws. In this paper, we introduce SANNS, a system for secure $k$-NNS that keeps client's query and the search result confidential. SANNS comprises two protocols: an optimized linear scan and a protocol based on a novel sublinear time clustering-based algorithm. We prove the security of both protocols in the standard semi-honest model. The protocols are built upon several state-of-the-art cryptographic primitives such as lattice-based additively homomorphic encryption, distributed oblivious RAM, and garbled circuits. We provide several contributions to each of these primitives which are applicable to other secure computation tasks. Both of our protocols rely on a new circuit for the approximate top-$k$ selection from $n$ numbers that is built from $O(n + k^2)$ comparators. We have implemented our proposed system and performed extensive experimental results on four datasets in two different computation environments, demonstrating more than $18-31\times$ faster response time compared to optimally implemented protocols from the prior work. Moreover, SANNS is the first work that scales to the database of 10 million entries, pushing the limit by more than two orders of magnitude.Comment: 18 pages, to appear at USENIX Security Symposium 202

Privacy-preserving information hiding and its applications

The phenomenal advances in cloud computing technology have raised concerns about data privacy. Aided by the modern cryptographic techniques such as homomorphic encryption, it has become possible to carry out computations in the encrypted domain and process data without compromising information privacy. In this thesis, we study various classes of privacy-preserving information hiding schemes and their real-world applications for cyber security, cloud computing, Internet of things, etc. Data breach is recognised as one of the most dreadful cyber security threats in which private data is copied, transmitted, viewed, stolen or used by unauthorised parties. Although encryption can obfuscate private information against unauthorised viewing, it may not stop data from illegitimate exportation. Privacy-preserving Information hiding can serve as a potential solution to this issue in such a manner that a permission code is embedded into the encrypted data and can be detected when transmissions occur. Digital watermarking is a technique that has been used for a wide range of intriguing applications such as data authentication and ownership identification. However, some of the algorithms are proprietary intellectual properties and thus the availability to the general public is rather limited. A possible solution is to outsource the task of watermarking to an authorised cloud service provider, that has legitimate right to execute the algorithms as well as high computational capacity. Privacypreserving Information hiding is well suited to this scenario since it is operated in the encrypted domain and hence prevents private data from being collected by the cloud. Internet of things is a promising technology to healthcare industry. A common framework consists of wearable equipments for monitoring the health status of an individual, a local gateway device for aggregating the data, and a cloud server for storing and analysing the data. However, there are risks that an adversary may attempt to eavesdrop the wireless communication, attack the gateway device or even access to the cloud server. Hence, it is desirable to produce and encrypt the data simultaneously and incorporate secret sharing schemes to realise access control. Privacy-preserving secret sharing is a novel research for fulfilling this function. In summary, this thesis presents novel schemes and algorithms, including: • two privacy-preserving reversible information hiding schemes based upon symmetric cryptography using arithmetic of quadratic residues and lexicographic permutations, respectively. • two privacy-preserving reversible information hiding schemes based upon asymmetric cryptography using multiplicative and additive privacy homomorphisms, respectively. • four predictive models for assisting the removal of distortions inflicted by information hiding based respectively upon projection theorem, image gradient, total variation denoising, and Bayesian inference. • three privacy-preserving secret sharing algorithms with different levels of generality

Framework for privacy-aware content distribution in peer-to- peer networks with copyright protection

The use of peer-to-peer (P2P) networks for multimedia distribution has spread out globally in recent years. This mass popularity is primarily driven by the efficient distribution of content, also giving rise to piracy and copyright infringement as well as privacy concerns. An end user (buyer) of a P2P content distribution system does not want to reveal his/her identity during a transaction with a content owner (merchant), whereas the merchant does not want the buyer to further redistribute the content illegally. Therefore, there is a strong need for content distribution mechanisms over P2P networks that do not pose security and privacy threats to copyright holders and end users, respectively. However, the current systems being developed to provide copyright and privacy protection to merchants and end users employ cryptographic mechanisms, which incur high computational and communication costs, making these systems impractical for the distribution of big files, such as music albums or movies.El uso de soluciones de igual a igual (peer-to-peer, P2P) para la distribución multimedia se ha extendido mundialmente en los últimos años. La amplia popularidad de este paradigma se debe, principalmente, a la distribución eficiente de los contenidos, pero también da lugar a la piratería, a la violación del copyright y a problemas de privacidad. Un usuario final (comprador) de un sistema de distribución de contenidos P2P no quiere revelar su identidad durante una transacción con un propietario de contenidos (comerciante), mientras que el comerciante no quiere que el comprador pueda redistribuir ilegalmente el contenido más adelante. Por lo tanto, existe una fuerte necesidad de mecanismos de distribución de contenidos por medio de redes P2P que no supongan un riesgo de seguridad y privacidad a los titulares de derechos y los usuarios finales, respectivamente. Sin embargo, los sistemas actuales que se desarrollan con el propósito de proteger el copyright y la privacidad de los comerciantes y los usuarios finales emplean mecanismos de cifrado que implican unas cargas computacionales y de comunicaciones muy elevadas que convierten a estos sistemas en poco prácticos para distribuir archivos de gran tamaño, tales como álbumes de música o películas.L'ús de solucions d'igual a igual (peer-to-peer, P2P) per a la distribució multimèdia s'ha estès mundialment els darrers anys. L'àmplia popularitat d'aquest paradigma es deu, principalment, a la distribució eficient dels continguts, però també dóna lloc a la pirateria, a la violació del copyright i a problemes de privadesa. Un usuari final (comprador) d'un sistema de distribució de continguts P2P no vol revelar la seva identitat durant una transacció amb un propietari de continguts (comerciant), mentre que el comerciant no vol que el comprador pugui redistribuir il·legalment el contingut més endavant. Per tant, hi ha una gran necessitat de mecanismes de distribució de continguts per mitjà de xarxes P2P que no comportin un risc de seguretat i privadesa als titulars de drets i els usuaris finals, respectivament. Tanmateix, els sistemes actuals que es desenvolupen amb el propòsit de protegir el copyright i la privadesa dels comerciants i els usuaris finals fan servir mecanismes d'encriptació que impliquen unes càrregues computacionals i de comunicacions molt elevades que fan aquests sistemes poc pràctics per a distribuir arxius de grans dimensions, com ara àlbums de música o pel·lícules

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas