High Efficiency Video Coding Streaming Research Articles

A Crypto-Steganography Approach for Hiding Ransomware within HEVC Streams in Android IoT Devices.

Steganography is a vital security approach that hides any secret content within ordinary data, such as multimedia. This hiding aims to achieve the confidentiality of the IoT secret data; whether it is benign or malicious (e.g., ransomware) and for defensive or offensive purposes. This paper introduces a hybrid crypto-steganography approach for ransomware hiding within high-resolution video frames. This proposed approach is based on hybridizing an AES (advanced encryption standard) algorithm and LSB (least significant bit) steganography process. Initially, AES encrypts the secret Android ransomware data, and then LSB embeds it based on random selection criteria for the cover video pixels. This research examined broad objective and subjective quality assessment metrics to evaluate the performance of the proposed hybrid approach. We used different sizes of ransomware samples and different resolutions of HEVC (high-efficiency video coding) frames to conduct simulation experiments and comparison studies. The assessment results prove the superior efficiency of the introduced hybrid crypto-steganography approach compared to other existing steganography approaches in terms of (a) achieving the integrity of the secret ransomware data, (b) ensuring higher imperceptibility of stego video frames, (3) introducing a multi-level security approach using the AES encryption in addition to the LSB steganography, (4) performing randomness embedding based on RPS (random pixel selection) for concealing secret ransomware bits, (5) succeeding in fully extracting the ransomware data at the receiver side, (6) obtaining strong subjective and objective qualities for all tested evaluation metrics, (7) embedding different sizes of secret data at the same time within the video frame, and finally (8) passing the security scanning tests of 70 antivirus engines without detecting the existence of the embedded ransomware.

Novel Ransomware Hiding Model Using HEVC Steganography Approach

Ransomware is considered one of the most threatening cyberattacks. Existing solutions have focused mainly on discriminating ransomware by analyzing the apps themselves, but they have overlooked possible ways of hiding ransomware apps and making them difficult to be detected and then analyzed. Therefore, this paper proposes a novel ransomware hiding model by utilizing a block-based High-Efficiency Video Coding (HEVC) steganography approach. The main idea of the proposed steganography approach is the division of the secret ransomware data and cover HEVC frames into different blocks. After that, the Least Significant Bit (LSB) based Hamming Distance (HD) calculation is performed amongst the secret data’s divided blocks and cover frames. Finally, the secret data bits are hidden into the marked bits of the cover HEVC frame-blocks based on the calculated HD value. The main advantage of the suggested steganography approach is the minor impact on the cover HEVC frames after embedding the ransomware while preserving the histogram attributes of the cover video frame with a high imperceptibility. This is due to the utilization of an adaptive steganography cost function during the embedding process. The proposed ransomware hiding approach was heavily examined using subjective and objective tests and applying different HEVC streams with diverse resolutions and different secret ransomware apps of various sizes. The obtained results prove the efficiency of the proposed steganography approach by achieving high capacity and successful embedding process while ensuring the hidden ransomware’s undetectability within the video frames. For example, in terms of embedding quality, the proposed model achieved a high peak signal-to-noise ratio that reached 59.3 dB and a low mean-square-error of 0.07 for the examined HEVC streams. Also, out of 65 antivirus engines, no engine could detect the existence of the embedded ransomware app.

Cybersecurity framework of hybrid watermarking and selective encryption for secure HEVC communication

Recently, the digital multimedia cybersecurity has become a research topic of interest due to the fast development of real-time multimedia applications over public networks such as the Internet. Therefore, this research paper introduces an efficient cybersecurity framework for protecting the high-efficiency video coding (HEVC) frames. The suggested selective cybersecurity HEVC framework employs a robust hybrid technique based on watermarking and selective encryption for maintaining confidentiality and achieving copyright protection of the transmitted HEVC information. The watermarking method employs the Homomorphic transform and singular value decomposition in the discrete wavelet transform to increase the immunity of watermarked HEVC streams to attacks. Moreover, the selective encryption technique uses the Chaotic logistic map for encrypting the motion vector difference and the discrete cosine transform sign bits to provide the feature of HEVC format compliance with low encryption overhead cost. An extensive security investigation is carried out for the proposed selective HEVC cybersecurity framework. The obtained experimental outcomes ensure and validate the effectiveness of the selective HEVC cybersecurity framework for HEVC sequences transmission.

Optical Bit-Plane-Based 3D-JST Cryptography Algorithm With Cascaded 2D-FrFT Encryption for Efficient and Secure HEVC Communication

The rapid growth of multimedia communication systems has expanded the High-Efficiency Video Coding (HEVC) security applications precipitously. Therefore, there is an urgent, elevated need to protect and secure the HEVC content during streaming and communication over insecure channels to ensure the privacy of HEVC data against intruders and attackers. This paper introduces an optical HEVC cipher algorithm based on bit-plane 3D-JST (Three-Dimensional Jigsaw Transform) and multistage 2D-FrFT (Two-Dimensional Fractional Fourier Transform) encryption. The main advantage of employing 3D-JST is its unitary transform that has an inverse transform used to reorganize the HEVC frame-blocks in an indiscriminately way. The proposed algorithm embraces the cascaded 2D-FrFT encryption in the optical domain using a single arbitrary phase code; to be executed all optically with a lone lens. The suggested algorithm utilizes the two 2D-FrFT stages with distinct kernels in mutually dimensions separated by employing the arbitrary phase code. A foregoing bit-plane permutation stage is conducted on the input HEVC frames before the 3D-JST and 2D-FrFT processes to accomplish a high robustness and security level. To validate the efficacy of the proposed cryptography algorithm for secure HEVC streaming, a comprehensive evaluation framework has been introduced and followed to (a) test HEVC streams against different statistical cryptographic metrics, (b) compare the proposed algorithm with recent related works whether optical-based or digital-based algorithms and (c) study the impact of different security attacks on its performance. The evaluation results show a secure and efficient proposed cryptography algorithm that outperforms the conventional and related cryptography algorithms in terms of all examined evaluation metrics.

Resource Management for Power-Constrained HEVC Transcoding Using Reinforcement Learning

The advent of online video streaming applications and services along with the users’ demand for high-quality contents require High Efficiency Video Coding (HEVC), which provides higher video quality and more compression at the cost of increased complexity. On one hand, HEVC exposes a set of dynamically tunable parameters to provide trade-offs among Quality-of-Service (QoS), performance, and power consumption of multi-core servers on the video providers’ data center. On the other hand, resource management of modern multi-core servers is in charge of adapting system-level parameters, such as operating frequency and multithreading, to deal with concurrent applications and their requirements. Therefore, efficient multi-user HEVC streaming necessitates joint adaptation of application- and system-level parameters. Nonetheless, dealing with such a large and dynamic design space is challenging and difficult to address through conventional resource management strategies. Thus, in this work, we develop a multi-agent Reinforcement Learning framework to jointly adjust application- and system-level parameters at runtime to satisfy the QoS of multi-user HEVC streaming in power-constrained servers. In particular, the design space, composed of all design parameters, is split into smaller independent sub-spaces. Each design sub-space is assigned to a particular agent so that it can explore it faster, yet accurately. The benefits of our approach are revealed in terms of adaptability and quality (with up to to $4\times$ 4 × improvements in terms of QoS when compared to a static resource management scheme), and learning time ( $6 \times$ 6 × faster than an equivalent mono-agent implementation). Finally, we show that the power-capping techniques formulated outperform the hardware-based power capping with respect to quality.

A Novel Hybrid Cryptosystem for Secure Streaming of High Efficiency H.265 Compressed Videos in IoT Multimedia Applications

In this modernistic age of innovative technologies like big data processing, cloud computing, and Internet of things, the utilization of multimedia information is growing daily. In contrast to other forms of multimedia, videos are extensively utilized and streamed over the Internet and communication networks in numerous Internet of Multimedia Things (IoMT) applications. Consequently, there is an immense necessity to achieve secure video transmission over modern communication networks due to the third-party exploitation and falsification of transmitted and stored digital multimedia data. The present methods for secure communication of multimedia content between clouds and mobile devices have constraints in terms of processing load, memory support, data size, and battery power. These methods are not the optimum solutions for large-sized multimedia content and are not appropriate for the restricted resources of mobile devices and clouds. The High-Efficiency Video Coding (HEVC) is the latest and modern video codec standard introduced for efficiently storing and streaming of high-resolution videos with suitable size and higher quality. In this paper, a novel hybrid cryptosystem combining DNA (Deoxyribonucleic Acid) sequences, Arnold chaotic map, and Mandelbrot sets is suggested for secure streaming of compressed HEVC streams. Firstly, the high-resolution videos are encoded using the H.265/HEVC codec to achieve efficient compression performance. Subsequently, the suggested Arnold chaotic map ciphering process is employed individually on three channels (Y, U, and V) of the compressed HEVC frame. Then, the DNA encoding sequences are established on the primary encrypted frames resulted from the previous chaotic ciphering process. After that, a modified Mandelbrot set-based conditional shift process is presented to effectively introduce confusion features on the Y, U, and V channels of the resulted ciphered frames. Massive simulation results and security analysis are performed to substantiate that the suggested HEVC cryptosystem reveals astonishing robustness and security accomplishment in contrast to the literature cryptosystems.

A Two-Stage Approach for Robust HEVC Coding and Streaming

The increased compression ratios achieved by the High Efficiency Video Coding (HEVC) standard lead to reduced robustness of coded streams, with increased susceptibility to network errors and consequent video quality degradation. This paper proposes a method based on a two-stage approach to improve the error robustness of HEVC streaming, by reducing temporal error propagation in the case of frame loss. The prediction mismatch that occurs at the decoder after frame loss is reduced through the following two stages. First, at the encoding stage, the reference pictures are dynamically selected based on constraining conditions and Lagrangian optimization, which distributes the use of reference pictures, by reducing the number of prediction units that depend on a single reference. Second, at the streaming stage, a motion vector (MV) prioritization algorithm, based on spatial dependencies, selects an optimal subset of MVs to be transmitted, redundantly, as side information to reduce mismatched MV predictions at the decoder. The simulation results show that the proposed method significantly reduces the effect of temporal error propagation. Compared with the reference HEVC, the proposed reference picture selection method is able to improve the video quality at low-packet-loss rates (e.g., 1%) using the same bitrate, achieving quality gains up to 2.3 dB for 10% of packet loss ratio. It is shown, for instance, that the redundant MVs are able to boost the performance achieving quality gains of 3 dB when compared with the reference HEVC, at the cost using 4% increase in total bitrate.

Implementation of 4kUHD HEVC-content transmission

The Internet of things (IoT) has received a great deal of attention in recent years, and is still being approached with a wide range of views. At the same time, video data now accounts for over half of the internet traffic. With the current availability of beyond high definition, it is worth understanding the performance effects, especially for real-time applications. High Efficiency Video Coding (HEVC) aims to provide reduction in bandwidth utilisation while maintaining perceived video quality in comparison with its predecessor codecs. Its adoption aims to provide for areas such as television broadcast, multimedia streaming/storage, and mobile communications with significant improvements. Although there have been attempts at HEVC streaming, the literature/implementations offered do not take into consideration changes in the HEVC specifications. Beyond this point, it seems little research exists on real-time HEVC coded content live streaming. Our contribution fills this current gap in enabling compliant and real-time networked HEVC visual applications. This is done implementing a technique for real-time HEVC encapsulation in MPEG-2 Transmission Stream (MPEG-2 TS) and HTTP Live Streaming (HLS), thereby removing the need for multi-platform clients to receive and decode HEVC streams. It is taken further by evaluating the transmission of 4k UHDTV HEVC-coded content in a typical wireless environment using both computers and mobile devices, while considering well-known factors such as obstruction, interference and other unseen factors that affect the network performance and video quality. Our results suggest that 4kUHD can be streamed at 13.5 Mb/s, and can be delivered to multiple devices without loss in perceived quality.

The impact of network impairment on quality of experience (QoE) in H.265/HEVC video streaming

Users of modern portable consumer devices (smartphones, tablets etc.) expect ubiquitous delivery of high quality services, which fully utilise the capabilities of their devices. Video streaming is one of the most widely used yet challenging services for operators to deliver with assured service levels. This challenge is more apparent in wireless networks where bandwidth constraints and packet loss are common. The lower bandwidth requirements of High Efficiency Video Coding (HEVC) provide the potential to enable service providers to deliver high quality video streams in low-bandwidth networks; however, packet loss may result in greater damage in perceived quality given the higher compression ratio. This work considers the delivery of HEVC encoded video streams in impaired network environments and quantifies the effects of network impairment on HEVC video streaming from the perspective of the end user. HEVC encoded streams were transmitted over a test network with both wired and wireless segments that had imperfect communication channels subject to packet loss. Two different error concealment methods were employed to mitigate packet loss and overcome reference decoder robustness issues. The perceptual quality of received video was subjectively assessed by a panel of viewers. Existing subjective studies of HEVC quality have not considered the implications of network impairments. Analysis of results has quantified the effects of packet loss in HEVC on perceptual quality and provided valuable insight into the relative importance of the main factors observed to influence user perception in HEVC streaming. The outputs from this study show the relative importance and relationship between those factors that affect human perception of quality in impaired HEVC encoded video streams. The subjective analysis is supported by comparison with commonly used objective quality measurement techniques. Outputs from this work may be used in the development of quality of experience (QoE) oriented streaming applications for HEVC in loss prone networks.

HEVStream: a framework for streaming and evaluation of high efficiency video coding (HEVC) content in loss-prone networks

High Efficiency Video Coding (HEVC) is the next generation video compression standard currently under development within the ITU-T/ISO sponsored Joint Collaborative Team on Video Coding (JCT-VC). The standardization, and eventual adoption, of HEVC will contribute significantly to the future development of many consumer devices. Areas such as broadcast television, multimedia streaming, mobile communications and multimedia/video content storage will all be impacted by implementation of the emerging HEVC standard. Up to this point in time the research focus of HEVC has been on improvements to video compression efficiency and little work has been conducted into streaming of HEVC. In this work we consider the practical barriers to HEVC streaming in realistic environments and propose HEVStream, a streaming and evaluation framework for HEVC encoded content. Our framework fills the current gap in enabling networked HEVC visual applications and permits the implementation, testing and evaluation of HEVC encoded video streaming under a range of packet loss, bandwidth restriction and network delay scenarios in a realistic testbed environment. We provide a basic error concealment method for HEVC to overcome limitations within the decoder and an RTP packetisation format for HEVC Network Abstraction Layer (NAL) units. Comprehensive results of HEVC streaming experiments under various network circumstances are reported. These results provide an insight into the reduction in picture quality, measured as peak signal to noise ratio (PSNR), that can be expected under a wide range of network constraint and packet loss conditions. We report an average loss of 3.61dB when a bandwidth reduction of 10% is applied. We believe that this work will be amongst the first to report on successful design and implementation of HEVC network applications, and evaluation of the effects of network constraints or limitations on the quality of HEVC encoded video streams.