In recent years, people tend to upload images to cloud servers, which provide storage and retrieval functions. To prevent users’ privacy from leaking to the server, research on cipher-image retrieval has attracted much attention. This work presents a novel encrypted image retrieval method. With this scheme, we perform encryption during the JPEG compression process by applying 16×16 DCT (Discrete Cosine Transform) for blocks’ transformation, followed by coefficients distribution and 8×8 blocks’ permutation. For the retrieval part, when an encrypted query image is sent by an authorized user, the server extracts its DCT histograms as features and inputs them into our trained network model, which incorporates transpose Multilayer perceptron modules ($Transpose$$MLP$), for retrieval. Experimental results show that our scheme, compared with related schemes, can improve the retrieval performance significantly, when ensuring compression friendliness and no feature information leakage. Moreover, our scheme enables cipher-image retrieval from multiple image owners.

In recent years, image encryption has been broadly researched. Since a large proportion of images on Internet are compressed, and JPEG is the most widely adopted standards for image compression, a variety of joint image compression and encryption algorithms have been proposed. JPEG image encryption uses signal processing techniques as well as cryptographic techniques in different stages of the JPEG compression process. Based on the location where the encryption is taken place, these algorithms can be generally classified into three major categories: pre‐compression encryption algorithms, in‐compression encryption algorithms, and post‐compression encryption algorithms, which correspond to conduct encryption operations before, during, and after the compression process. From this perspective of classification, the authors give a comprehensive survey on representative image encryption algorithms of each type, and show their properties and limitations. Some of the most recent encryption schemes that achieve protection at various positions of the compression process are selected for comparison, which are two pre‐compression encryption algorithms, four in‐compression encryption algorithms, and two post‐compression encryption algorithms. Possible future research directions on designing joint JPEG compression and encryption schemes are provided in the end, which may facilitate solving application scenario‐oriented JPEG security problems with new technologies.

For joint image compression and encryption schemes, the encryption power and compression efficiency are commonly two contradictory things. In this paper, we propose a new joint image compression and encryption scheme based on a lossy JPEG standard, which aims at encryption power's enhancement, on the premise of maintaining the JPEG's compression efficiency. The proposed scheme is image-content-adaptive, since the secret encryption key is generated from the plain image using the BLAKE2 hash algorithm. Three encryption operations are contained in our scheme, alternating new orthogonal transforms transformation, dc coefficients encryption, and ac coefficients encryption. To save the cost for transmitting different encryption keys each time to decoder for decryption when the plain image changes, we propose embedding the encryption key into the entropy-encoded bitstream of some ac coefficients, and the whole embedding procedure is controlled by another secret key called the embedding key. Extensive experiments are conducted to show that our encryption scheme is JPEG friendly, and has good confusion and diffusion properties. Detailed security analysis is also given to illustrate the proposed scheme's persistence to various cryptanalysis strategies.

In this paper, we propose a novel joint image compression and encryption technique where an annoying image can still be recovered even without the encryption key. Our work is based on JPEG standard. By embedding encryption algorithm at the transformation stage, we realize image encryption and compression together with controllable image quality. Instead of using the 8×8 discrete cosine transform (DCT) alone for transformation, we develop new orthogonal transforms by introducing sign-flips into the butterflies of DCT's flow-graph structure, and then employ them alternatively in JPEG's transformation stage according to a secret key. By carefully selecting the butterflies for sign-flipping, we can control the visual quality of the encrypted images. Finally, a detailed security analysis of our proposed encryption algorithm is presented to show its resistance to various attacks, such as cryptographic attack, replacement attack and statistical model-based attack.

In this paper, we conduct an in-depth study on the feasibility of using network coding to ameliorate the content availability of BitTorrent swarms. We first perform mathematical analysis on the potential improvement in the content availability and bandwidth utilization induced by two existing network coding schemes. It is found that these two coding schemes either incur a very high coding complexity and disk operation overhead or cannot effectively leverage the potential of improving the content availability. In this regard, we propose a simple sparse network coding scheme in which both the drawbacks mentioned before are precluded. To accommodate the proposed coding scheme into BitTorrent, a new block scheduling algorithm is also developed based on the original rarest-first block scheduling policy of BitTorrent. Through extensive simulations and performance evaluations, we show that the proposed coding scheme is very effective in terms of improving the content availability of BitTorrent swarms when compared with some existing methods.

Peer-to-peer (P2P) and multicast approaches are two common transmission strategies to provide scalable and cost efficient solutions for video-on-demand (VoD) services. The former approach requires small server resources and provides a negligible delay to users, but the bandwidth requirement inside the network will be rapidly increased when more customers join the video session. On the other hand, if the system simply uses a multicast scheme to deliver a video, customers will experience a noticeable delay before watching the video whereas the overall bandwidth requirement will not be significantly increased. In this paper, a new transmission policy denoted peer-to-peer batching (PPB) policy is proposed to efficiently deliver video data in a large scale VoD system by exploiting the multicast capability of the network and P2P paradigm. To avoid the disruption of services, the fault tolerance and recovery mechanism is also developed for PPB. In addition, in order to further improve the scalability of the system, a distributed PPB (DPPP) is also proposed. We then develop a mathematical model to evaluate the performance of each of our proposed policies analytically. Based on this model, system designers are able to study various design options as well as perform system dimensioning. Both analytical and simulation results show that the proposed scheme achieves better system performance compared with existing schemes.

This paper presents a new collaborative peer-to-peer (P2P) streaming framework for heterogeneous bandwidth capacity of clients. The proposed architecture aims for two primary goals: (1) providing higher streaming quality by making best use of the extra available bandwidth that might exist among heterogeneous clients and (2) providing robustness and resilience to high churn rate of peers by introducing redundancy, both in network paths (multisender overlay) and data (multilayered video content). For achieving these goals, we employ a gossip-based data-driven scheme for partnership formation and layered video coding for bandwidth adaptivity. To solve multilayer bitstream allocation problem, we proposed two algorithms, namely optimized transmission policy and graceful degradation scheme algorithms. The proposed system has a complete self-regulation and in a decentralized fashion. Extensive simulations show that the proposed system achieves higher quality of service through peer-assisted streaming and layered video coding. The results also show that the system outperforms some previous schemes in system overhead and reliability for dynamic node behavior.

Recently, a new image scrambling (i.e., encryption) scheme without bandwidth expansion was proposed based on two-dimensional discrete prolate spheroidal sequences. A comprehensive cryptanalysis is given here on this image scrambling scheme, showing that it is not sufficiently secure against various cryptographical attacks including ciphertext-only attack, known/chosen-plaintext attack, and chosen-ciphertext attack. Detailed cryptanalytic results suggest that the image scrambling scheme can only be used to realize perceptual encryption but not to provide content protection for digital images.

Peer-to-peer (P2P) streaming has become a promising approach for disseminating streaming media content from the server to a large number of interested clients. It still faces many challenges, however, such as high churn rate of peer clients, uplink bandwidth constraints of participating peers, and heterogeneity of client capacities. To resolve these issues, this paper presents a new P2P streaming framework that combines with the advantages of both mesh-based multisource overlay networks and scalable video coding techniques, specifically with multiple description coding (MDC), to improve the streaming quality of participating clients. In this paper, an optimized allocation policy (OAP) algorithm was proposed for multidescriptions allocation. Extensive simulations show that the proposed system achieves higher quality of service by peer-assisted cooperative streaming and MDC coding. In addition, we investigate an efficient cooperative caching mechanism for streaming service. The target is to provide low-latency and high-quality services by virtue of peer collaboration. The storage and replacement of caching content are based on a segment-based strategy. Through comparison, we demonstrate the effectiveness of the proposed scheme and compare with the traditional LRUF scheme through extensive experiments over large Internet-like topologies. Results show that the system outperforms some previous schemes in resource utilization and is more robust and resilient to node departure, which demonstrate that it is well suited for quality adaptive cooperative streaming applications.

Recently, peer-to-peer (P2P) overlay networks have become popular and many P2P applications such as file sharing and content distribution have been introduced. Naturally, P2P cooperative caching schemes for streaming were introduced. However, these approaches manifest inefficiency of cache utilization due to inappropriate cache replacement algorithms, and no consideration of dynamic membership changes of peer nodes. In this paper, we investigate an efficient cooperative caching mechanism for VOD streaming service over P2P overlay networks. The target of the system is to provide low-latency and high-quality services by virtue of pees' collaboration. The storage and replacement of caching content are based on segment-based strategy. And a utility-based fine-grained cooperative cache (DUFC) policy was proposed for cache replacement. We demonstrate the effectiveness of the proposed scheme and compare with traditional LRUF scheme through extensive simulation experiments over large, Internet-like topologies.

Early departure of customers during video playback brings a great impact on the design of a peer-to-peer (P2P) video-on-demand (VoD) system, especially on the system bandwidth requirement and the need for a well-defined fault exception mechanism. In this paper, we develop an analytical model to evaluate how the system parameters such as bandwidth requirement and batching time in a P2P batching system are affected when early departure behavior is taken into account. In addition, a fault exception mechanism is also proposed. Computer simulations are performed to verify the correctness of the model. The results show that the system resources can be utilized more effectively when the customer departure behavior is captured into the system.

In this paper, some existing perceptual encryption algorithms of MPEG videos are reviewed and some problems, especially security defects of two recently proposed MPEG-video perceptual encryption schemes, are pointed out. Then, a simpler and more effective design is suggested, which selectively encrypts fixed-length codewords in MPEG-video bit streams under the control of three perceptibility factors. The proposed design is actually an encryption configuration that can work with any stream cipher or block cipher. Compared with the previously-proposed schemes, the new design provides more useful features, such as strict size-preservation, on-the-fly encryption and multiple perceptibility, which make it possible to support more applications with different requirements. In addition, four different measures are suggested to provide better security against known/chosen-plaintext attacks.

Live peer-to-peer (P2P) streaming has become a promising approach to broadcasting non-interactive streaming media content from a server to a large number of interested clients. It still faces many challenges, however, such as high churn rate of peer clients, uplink bandwidth constrains of participating peers, and heterogeneity of client capacities. This paper presents LSONet, a collaborative peer-to-peer streaming framework for scalable layer-encoded bit streams. For achieving higher streaming quality and resilient to peer churn, this paper employs a mesh-based data-driven scheme for partnership formation, and proposes two algorithms, optimal transmission policy (DTP) and graceful degradation scheme (GDS), for multi-layers allocation. Extensive simulations show that LSONet achieves higher quality of service thanks to peer-assisted streaming and layered video coding. Also, through comparison, results show that the system outperforms previous scheme in resource utilization and control overhead

In providing video-on-demand services in multicast environment, a broadcasting technique like skyscraper is very efficient for serving a very popular video in terms of resource requirement. However, a multicasting method like patching will achieve better performance if the video is not popular enough. Since there may not be a clear distinction between very popular and popular videos, an analytical model is developed in this paper to select an appropriate delivery scheme for the videos according to both the popularity of videos and the customer reneging behavior. The result shows that not only is the overall bandwidth of the system minimized, but a preset quality of service is also provided for each customer when using our proposed scheme.

In this paper, an optimal channel allocation is developed for a large scale video-on-demand system to allocate transmission resources according to the popularity of videos. In the proposed framework, a video will be delivered to customers through one of the three channels, namely broadcast, multicast, and unicast, depending on whether the video is very hot, hot or cold, respectively, A novel algorithm is developed to allocate the appropriate delivery channel for the video according to its popularity so that not only the overall bandwidth of the system is minimized but also a preset quality of service (QoS) is provided for each customer.

A new batching policy is proposed for providing true VoD services in multicast VoD systems. Instead of batching the user requests, we serve the new customer with a dedicated stream immediately and then try to merge the customers for the same movie in progress by doubling the transmission rate. Both analytical methods and computer simulations have been performed to evaluate the proposed batching scheme in terms of bandwidth and buffer requirement as well as the blocking probability in multicast VoD systems. Compared with a system without batching, the result shows that over 90% of bandwidth reduction can be obtained. It is shown that only 90 streams are required for one movie to support about 1440 concurrent customers in 2 hours with less than 5% blocking probability.

In this paper, a digital halftoning method is proposed based on a recently-proposed multiscale error diffusion technique for digital halftoning. It can definitely improve the diffusion performance by effectively removing pattern noise and eliminating boundary and 'blackhole' effects. A dot-overlap compensation scheme is also proposed to eliminate the bias in the gray scale of the printed images.

In this paper, a new fast block matching algorithm is developed for motion estimation. The feature of the new algorithm comes from the center-biased checking concept and the trend of pixel movements. In this algorithm, we develop two criteria for the searching algorithm to be adapted to local characteristics of the test block. Simulation results show that the total search positions are about 20% fewer than TSS while the MSE performance is better than TSS and very close to the full search method.

In this paper, a hierarchical model is derived for MPEG video. This model is developed so as to represent the bit-rate variations of MPEG video at two different time scales/levels: scene level and frame level. Various evaluations show that the proposed model not only matches well the statistical characteristics with the real MPEG video but also predicts accurately the network performance of an ATM multiplexer.

In this paper, we first investigate the impacts of different interleaving and synchronization schemes on the performance of an ATM multiplexer using real MPEG data. A source scheduling method is then developed to improve the performance of the multiplexer. Experiment results show that the level of burstiness for the aggregated MPEG traffic is reduced and the network performance in terms of cell loss probability and statistical multiplexing gain is greatly enhanced.

In this paper, a dynamic addressing scheme (DAVQ) is introduced for image vector quantization. In the proposed system, the dynamic address obtained by two-stage searching will be transmitted instead of the absolute address in conventional VQ systems. Simulation results demonstrate that a significant savings in bit rate is acquired when compared with the standard VQ system.

A new scene change detection algorithm is developed for MPEG encoded video sequences. The proposed method is very simple that it only requires the bit-rate information at macroblock level as well as the number of various motion-predicted blocks for detection. Those information can be extracted easily from the encoded bit-stream without decompression. Simulation results on different sequences show that the proposed algorithm is effective for detecting abrupt scene changes in MPEG video.

In this paper, a dynamic addressing scheme (DAVQ) is introduced for image vector quantization. It is a variable rate coding scheme that exploits the interblock correlation to minimize the bit-rate for a given fidelity. Each pattern matching of the DAVQ is through a two-stage searching. It first searches the previously used codewords according to a predefined 2-D spatial scanning path and then continues the search in the remaining of the codebook. At each instant of encoding, it may be envisaged that a virtual 2-D codebook of ever adapting array of codewords is naturally evolved with respect to each individual input block. Simulation results demonstrate that a general saving of around 40% in bit-rate is acquired.

Motion estimation/compensation techniques are extensively used in video compression because of their abilities to exploit the high temporal correlation between successive frames of an image sequence. We first propose a new matching criterion called bit-plane matching (BPM) for distance measurement in the block matching algorithm. This criterion not only considers the magnitude but also the directive information of the pixel elements in the block. A simple adaptive block matching algorithm is also developed to adjust the search origin and search range at a block-by-block basis. Simulation results show that the proposed algorithm achieves similar MSE performance for motion-predicted images but requires about 8 times less the number of computations than the full-search method.

In this paper a two-layer MPEG video coding algorithm is presented for video communications over ATM networks. A new classification method is proposed to partition image data into two layers with different priorities. A study on the statistical characteristics of the output bit-stream such as bit-rate distribution and autocorrelation at both bit-level and cell-level is given in the paper.

In this paper, a new order-8 dyadic transform (DT) is proposed for image compression. The proposed DT can be computed using a fast structural algorithm with operations of addition and binary shift only. Performance evaluations using a statistical model and real images show that the proposed DT performs better than the two DTs proposed by Lo and Cham and very close to DCT. Simulation results also show that there is a certain degree of compatibility between DCT and the proposed DT. In other words, DCT can be replaced by the proposed DT in existing image coding systems with little degradation in image quality.

A simple coding algorithm called the predictive mean search (PMS) algorithm is proposed for vector quantization of images. The proposed PMS algorithm, which exploits the interblock correlation, requires less computation than several existing VQ encoding algorithms and also achieves a higher compression ratio than the standard VQ scheme.>