VQProtect: Lightweight Visual Quality Protection for Error-Prone Selectively Encrypted Video Streaming  
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1 Department of Computer Science, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan; [EMAIL_ADDRESS] (S.M.G. ); [EMAIL_ADDRESS] (S.A.)  
[PERSON]  
1 Department of Computer Science, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan; [EMAIL_ADDRESS] (S.M.G. ); [EMAIL_ADDRESS] (S.A.)  
[PERSON]  
3 Department of Information Security, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan; [EMAIL_ADDRESS] (S.A.)  
[PERSON]  
1 Department of Computer Science, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan; [EMAIL_ADDRESS] (S.M.G. ); [EMAIL_ADDRESS] (S.A.)  
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4 School of Computing and Mathematics, Keele University, Staffordshire ST5 5 GB, UK; [EMAIL_ADDRESS] (S.A.)  
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5 Department of Computer Science, Lahore College for Women University, Lahore 54000, Pakistan 55 Department of Computer Science, Lahore College for Women University, Lahore 54000  
to accommodate the channel's limited bandwidth and storage capacity. For example, the H.264/Advanced Video Coding (AVC) standard [2] remains a widely deployed codec in real-time video streaming applications. Despite the presence of codecs, there remains competition for bandwidth, which essentially depends on access to a sufficient spectrum. Prior licensed spectrum usage is usually quite uneven and depends heavily on the specific wireless applications and their market penetration. Within a Cognitive Radio Network (CRN) [3], an uneven and underutilized licensed spectrum resource can be exploited to speculatively acquire bandwidth for multimedia applications. By employing CRNs, secondary users (SUs) can flexibly analyze their data rates, sense and access those temporarily vacant bands to satisfy the desired data rates for reliable communication. Compared to traditional wireless network users, SUs can adjust their application parameters according to the network conditions to fulfill the need of various multimedia applications for better QoE [4]. Because CRN channels are a desirable type of wireless network for multimedia transmission, this has led CR to be considered as a potential candidate to be incorporated into 5G cellular networks [5]. CR technology, whether part of a 5G network or operating as an independent CRN network, for multimedia communications opens up a new paradigm in which mobile devices receive or transmit streamed video content in a temporarily vacant licensed band in an opportunistic manner. However, along with positive features, it remains risky to multicast confidential multimedia content in this way due to the open nature of wireless channels [6]. In addition to the risk to video content confidentiality and sensitivity, during all wireless transmission, including over CRN channels, channel impairments will ineluctably cause changes to the signal characteristics during transmission. The most common causes are noise and competing traffic across the channel, leading to signal attenuation, cross-talk, electromagnetic intrusions, and bandwidth restrictions [7]. As a result, error detection and correction are the key challenges in communication systems. Generally, error control coding for video applications is classified into four different methods: (1) Retransmission, (2) Error resilience, (3) Error concealment, and (4) Forward Error Correction (FEC) [8]. FEC is especially used in real-time multimedia applications when real-time data are needed and when the delay caused by retransmission requests is not tolerable. Random-error FEC [9] can be carried out as Block coding and Convolution coding. Block codes work on the data of fixed-sized blocks, whereas convolution codes work on bitstreams of arbitrary size. These codes are mostly used for error correction in real-time applications. Turbo code and the Viterbi algorithm are examples of convolution coding.