Media Cloud Research Articles

A land cover mapping algorithm for thin to medium cloud-covered remote sensing images using a level set method

ABSTRACT This paper proposed a new land cover mapping algorithm for remote sensing images under the presence of clouds. Here, we modelled the observed image as the weighted sum between the reflectances from the cloud-free image and clouds where weights depend on the degree of cloud contamination called the ‘cloud thickness’ map. Next, we represented the cloud thickness map using a level set function. Similarly, we also represented the land cover map as functions of different level set functions whose values indicate the class label. Next, the maximum a posteriori (MAP) criterion is employed where the most likely land cover and cloud thickness maps are chosen. Under the MAP criterion, the corresponding energy function whose values depend on the level set functions can be derived where the minimum energy point corresponds to the optimum land cover and cloud thickness maps. Since the level set functions are continuous, the optimum solution can be obtained by applying the calculus of variation where the gradient descent algorithm is employed. From the observation model, the cloud-free data can only be reconstructed only if thin to medium clouds are present since thick clouds can completely block the reflectance from the land cover materials. Thus, our algorithm is more suitable for thin to medium than thick cloud covers. Our synthesis and real cloud-contamination examples support our statement since our algorithm achieves significantly higher overall accuracies over other classification techniques, especially, in the thin to medium cloud contamination, and fails to recover the true land cover classes over the thick clouds.

COVID-19 DAN KEBEBASAN BEREKSPRESI DI INTERNET: MELIHAT REPRESI DIGITAL DALAM PEMBERITAAN TEMPO.CO

The presence of the Covid-19 pandemic and high internet penetration in Indonesia have also encouraged community activities, one of which is digital activism. The purpose of this article is to describe digital activism carried out in the midst of a pandemic that has received a lot of repressive measures in cyberspace. The approach used is media cloud content analysis of Tempo.co news related to digital repression in Indonesia from March to December 2020. Researchers processed data using Nvivo 12 Plus software, the data generated included crosstab and wordcloud analysis. The results showed that hacking and doxing attacks were the most discussed cases of digital repression on Tempo.co. In addition, law enforcement and law enforcement against democracy in danger are indicators of the highest issue in Tempo.co's reporting. While the wordcloud analysis shows quotes from the police and government, many words imply some form of performance from the Police and Government.

Impact of Indian and East Asian Summer Monsoons on the Diurnal Temperature Range of the Low-Latitude Highlands of China in the Rainy Season

Abstract This study investigates the impact of the Indian and East Asian summer monsoons on the diurnal temperature range (DTR) in the low-latitude highlands of China (CLLH) based on in situ DTR observations, ERA5 data, and numerical simulations. Diagnoses indicate that the DTR in the CLLH shows a significant positive correlation with the Indian summer monsoon (ISM) and a negative correlation with the East Asian summer monsoon (EASM). When a strengthened ISM occurs with a weakened EASM, an anomalous anticyclonic circulation with downward motion is excited over the CLLH. This anomalous circulation pattern increases the DTR in the rainy season by reducing the medium and high cloud cover in the CLLH. A weakened ISM with a strengthened EASM decreases the DTR over the CLLH in the rainy season. Numerical experiments help to verify this crucial physical process linking the variability of the ISM and EASM with the DTR in the CLLH. The model results further indicate that the covariability of ISM and EASM contributes most to the variability of the rainy season DTR in the CLLH, followed by the individual variability of the EASM; the smallest contribution to the rainy season DTR in the CLLH is the individual variability of the ISM.

Regional characteristics and exploitation potential of atmospheric water resources in China

AbstractThe atmospheric water resources (AWR) in China have evident regional characteristics. In order to scientifically and rationally exploit the AWR in different regions of China, we divided China into seven regions based on the ERA‐5, the CloudSat data, and so on. Such characteristics as water vapour, cloud characteristics, cloud water resources (CWR), precipitation efficiency of hydrometeors (PEh), and the exploitation potential of CWR were studied in this article. Some results in summer are shown. (a) There were relatively more precipitation, richer water vapour, stronger water vapour transport and convergence, more cloud covers, and relatively larger zones of rich total column cloud water content in China. Therefore, it is of important significance to study AWR in summer in China. (b) In respect of single‐layer clouds, low clouds were in the majority over the Tibetan Plateau (TP) and the southwest China (SW), medium clouds were predominant over the northern regions, and high clouds existed more over the central region (CR) and the southeast China (SE). The liquid water content (LWC) at each height of cloud was less than 800 mg·m−3 and decreased gradually with the increase in height in China. The convective development heights, the LWC at each altitude, and the frequencies of less LWCs over the northern regions were lower than those over the southern regions. The ice water content (IWC) at each height of cloud was less than 250 mg·m−3, and more than 96% of them were less than 100 mg·m−3. (c) CWR over the northeast China (NE), north China (NC), and CR were relatively rich, but with relatively low PEh, so there was relatively higher exploitation potential of CWR in these regions, followed by the northwest China (NW) and TP, and there was still some exploitation potential of CWR in SE and SW.

Media Cloud: Massive Open Source Collection of Global News on the Open Web

We present the first full description of Media Cloud, an open source platform based on crawling hyperlink structure in operation for over 10 years, that for many uses will be the best way to collect data for studying the media ecosystem on the open web. We document the key choices behind what data Media Cloud collects and stores, how it processes and organizes these data, and its open API access as well as user-facing tools. We also highlight the strengths and limitations of the Media Cloud collection strategy compared to relevant alternatives. We give an overview two sample datasets generated using Media Cloud and discuss how researchers can use the platform to create their own datasets.

A Multi-platform Approach to Monitoring Negative Dominance for COVID-19 Vaccine-Related Information Online.

The aim of this study was to test the appearance of negative dominance in COVID-19 vaccine-related information and activity online. We hypothesized that if negative dominance appeared, it would be a reflection of peaks in adverse events related to the vaccine, that negative content would attract more engagement on social media than other vaccine-related posts, and posts referencing adverse events related to COVID-19 vaccination would have a higher average toxicity score. We collected data using Google Trends for search behavior, CrowdTangle for social media data, and Media Cloud for media stories, and compared them against the dates of key adverse events related to COVID-19. We used Communalytic to analyze the toxicity of social media posts by platform and topic. While our first hypothesis was partially supported, with peaks in search behavior for image and YouTube videos driven by adverse events, we did not find negative dominance in other types of searches or patterns of attention by news media or on social media. We did not find evidence in our data to prove the negative dominance of adverse events related to COVID-19 vaccination on social media. Future studies should corroborate these findings and, if consistent, focus on explaining why this may be the case.

Privacy-Preserving Media Sharing with Scalable Access Control and Secure Deduplication in Mobile Cloud Computing

Benefiting from cloud computing and mobile devices, a huge number of media contents, such as videos are shared in mobile networks. Although scalable video coding can be utilized to provide flexible adaptation, the cloud poses a serious threat to media privacy. In this paper, we propose a privacy-preserving multi-dimensional media sharing scheme named SMACD in mobile cloud computing. First, each media layer is encrypted with an access policy based on attribute-based encryption, which guarantees media confidentiality as well as fine-grained access control. Then, we present a multi-level access policy construction with secret sharing scheme. It ensures that the mobile consumers who obtain a media layer at a higher access level must satisfy the access trees of its child layers at the lower access level, which is compatible with the characteristics of multi-dimensional media and also reduces the complexity of access policies. Moreover, we introduce decentralized key servers to achieve both intra-server and inter-server deduplication by associating different access policies into the same encrypted media. Finally, we conduct experimental evaluation on mobile device and cloud platform with real-world datasets. The results indicate that SMACD protects media privacy against cloud media center and unauthorized parties, while incurring less computational and storage cost.

Precipitation Isotopes Linked with High-Level Cloud Cover at Local and Regional Scales in the Asian Monsoon Edge Region

In monsoonal areas, the ocean transports water vapor to inland areas and affects the stable isotopes of precipitation in inland areas, leading to that stable isotopes of precipitation could be used as a medium to study large-scale water vapor cycles. Analysis of the characteristics of δ18O and δ2H indicates that stable isotopes of precipitation in the Shiyang River Basin (SRB) exhibit obvious seasonal changes. The slope and intercept of the local meteoric water line (LMWL) in summer and autumn are lower than those in spring and winter, which is similar to the typical monsoon climate zone, indicating that large-scale monsoon water vapor is the main source of precipitation in the SRB. Regional-scale (equatorial North Pacific) cloud cover and outgoing longwave radiation (OLR) have a stronger impact on the East Asian monsoon edge area, there is a significant negative correlation between cloud cover in the equatorial North Pacific and precipitation stable isotopes in the SRB, and there is a positive correlation between OLR in the equatorial North Pacific and precipitation stable isotopes in the SRB. The cloud cover on the fifth day before precipitation in the equatorial North Pacific has the greatest impact on precipitationδ18O in the SRB. In the region with the highest correlation coefficient (the equatorial North Pacific), the correlation between precipitation δ18O and high cloud cover is greater than that between precipitation δ18O and medium cloud cover or low cloud cover, indicating that cloud cover has the most significant influence on precipitation stable isotopes in the middle troposphere (3–8 km).

Mobile And Cloud Computing Based It Strategic Planning (Case Study: Primeone School Medan)

PrimeOne is one of the national school in Medan which has used IT application in its operational, however the IT applied hasn’t reached the maximum standard and caused the important information couldn’t be accessed personally by parents such as checking for the tuition fee paid, checking for the students study progress, etc. So that it might cause some parents object to send their kids to PrimeOne School. This shows that PrimeOne School needs to have good IT Strategic Planning so that the school can serve the best for parents and reach the operational goals effectively. There are some purposes in this research (1) Plan for the good IT Strategic Planning which gets along well with school vision, mission, goals and business process for the next 2 years, which is 2016-2017 period, (2) To gain the Information System and Information Technology solution also recommendation which can support school business strategy to increase the interest of parents and school competition. This research used several methods to analyze which are SWOT analysis, Potter Five Forces Analysis, CSF Analysis and Value Chain Analysis. From these analysis, information system strategy, information technology strategy and IS/IT management strategy are produced. The result of this research is a recommendation or suggestion which is portfolio application which can be used for PrimeOne. The conclusion from this research is PrimeOne School is at the Second Quadran where it is expected to enlarge the IS/IT strategy applied and produce IS/IT strategy suggestion ( Promotion Application with Social Media Cloud Computing, POS Mobile Application, Interactive Learning Application, Facility Application and develop network connection between the school buildings ) which will increase parents’ interest and school competition.

Covering #MeToo across the News Spectrum: Political Accusation and Public Events as Drivers of Press Attention

Garnering coverage across the political spectrum is a major challenge for burgeoning social movements. The #MeToo movement stands out due to the volume of attention it generated. Yet, it is unclear how news media across the partisan spectrum covered the movement using different sexual violence language markers, latent topic, and word choices and which accusations and events drove media attention. To examine this, we used Media Cloud to extract 17,877 news articles from nine media outlets across the political spectrum, containing specific n-grams or co-occurrences of (1) “metoo,” (2) “sexual misconduct,” (3) “sexual harassment,” and (4) “sexual assault” from October 2017 through February 2018. The analyses first examined whether language and attention differed across the ideological news ecology and then turned to time-series modeling of these discourses to examine what drove press coverage and structural topic modeling (STM) and term frequency-inverse document frequency (TF-IDF) analysis to understand latent topics and language usage. Findings reveal that (1) left-leaning media dedicated more relative attention across all topics—#MeToo, sexual misconduct, sexual harassment, and sexual assault—relative to centrist and right-leaning media. Moreover, across the right, left, and centrist media, the language markers “misconduct,” “harassment,” and “assault” decreased over the study period, while the mentions of #MeToo movement increased during the same period; (2) stories relating to entertainment and those accusing politicians, especially those belonging to the party in power at the Federal level, seemed to be by far the strongest driver of news media attention; and (3) we further observed partisan differences in topics of news coverage and language usage.

Observed and modelled cloud cover up to 6 km height at Station Nord in the high Arctic

AbstractWe present results from an analyses of cloud cover based on profiles of the attenuated backscatter coefficient from an 8‐year‐long data series (July 2011–April 2019). The observations are carried out in the high Arctic by a ceilometer with a maximum range setting of 7.7 km from the Villum Research Station at Station Nord, Greenland. Results show that the hourly cloud cover turned out to follow a U‐shaped rather than Gaussian‐like distribution. Annual and seasonal cloud cover variation is illustrated. The cloud cover is larger during the autumn and winter as compared to summer and spring. The cloud cover exhibits a substantial variation from year to year without a clear trend. The cloud cover during spring is low and decreasing between 2012 and 2017. The cloud cover during the autumn of 2016 is lowest compared to the other years. The observed cloud cover is compared to the cloud cover provided in the ERA5 reanalysis dataset. The cloud cover for low clouds and medium clouds are combined to represent a total height of 6 km. Both the observed and modelled cloud cover is larger during winter as compared to summer‐time cloud cover. The measured reduction in the cloud cover for the autumn of 2016 is present in the reanalysis data as well but the measured low cloud cover during spring is not apparent in the reanalysis data. Because the cloud cover distribution is U‐shaped rather than of a Gaussian nature, standard metrics are not applicable. We apply a generalized skill score that is developed for contingency tables or joint histograms. Three skill scores were calculated. It was found that for all three methods, skills for the predictability of the cloud cover by the ERA5 modelling is better for winter than summer and is poor during the spring.

Fentanyl panic goes viral: The spread of misinformation about overdose risk from casual contact with fentanyl in mainstream and social media

BackgroundFueled by misinformation, fentanyl panic has harmed public health through complicating overdose rescue while rationalizing hyper-punitive criminal laws, wasteful expenditures, and proposals to curtail vital access to pain pharmacotherapy. To assess misinformation about health risk from casual contact with fentanyl, we characterize its diffusion and excess visibility in mainstream and social media. MethodsWe used Media Cloud to compile and characterize mainstream and social media content published between January 2015 and September 2019 on overdose risk from casual fentanyl exposure. ResultsRelevant content appeared in 551 news articles spanning 48 states. Misinformed media reports received approximately 450,000 Facebook shares, potentially reaching nearly 70,000,000 users from 2015-2019. Amplified by erroneous government statements, misinformation received excess social media visibility by a factor of 15 compared to corrective content, which garnered fewer than 30,000 shares with potential reach of 4,600,000 Facebook users. ConclusionHealth-related misinformation continues to proliferate online, hampering responses to public health crises. More evidence-informed tools are needed to effectively challenge misinformed narratives in mainstream and social media.

A recent review and a taxonomy for multimedia application in Mobile cloud computing based energy efficient transmission

The mobile devices have entered the race of deploying high tech to the users but inherit a defect of limited battery storage. With the limitationof battery capacity, energy efficiency has been a major concern for Mobile Cloud Computing (MCC). The multimedia application comprises rich media that needs higher processing and computation, and the resource and computation are constrained. Energy-efficient transmission is a big concern because it equips the mobile device with high-end hardware components, but still, are far behind to the battery capacity and computation competence. This paper intends to introduce and investigate the different approaches/algorithms and tools that best fit to save resource utilization and energy consumption rationally. The algorithms like the Genetic Algorithm, Greedy scheduling algorithm, power-aware list-based scheduling, Offloading based task scheduling, media cloud distributed scheduling algorithm, etc. are discussed in this research. The data, Energy-efficient technique, and Cloud server response that defines each of the main components is introduced in this paper that concerns the implementation of the energy-efficient transmission in MCC. We propose these components that illustrate the workflow in the technology. A process when the data is perceived by the technique to adequately deliver a response to the mobile device. An energy-efficient transmission technique for MCC is a development towards the use of mobile cloud computing in this field working to counter the utilization of energy and resources that execute locally. This concept results in reducing the amount of data transmitted with the use of sharing the data externally between the tasks that will save energy. Through this paper, readers will understand the benefit of using the energy-efficient technique in the MCC. Also, the reader will understand the classification groups, validation criteria, future gaps of the 30 literature reviews about the technique, and how they intend to energy optimization in mobile devices.

Cooperative and efficient content caching and distribution mechanism in 5G network

This paper considers encoding caching and collaborative distribution issues jointly, and proposes a collaborative and efficient content caching and distribution mechanism; and based on the proposed scheme, an energy consumption model is established from the perspective of content caching and content distribution to optimize Energy efficiency of content caching and content distribution. In addition, this paper proposes a cache placement algorithm based on heuristic greedy algorithm to solve this energy efficiency optimization problem by optimizing cache placement. Finally, the simulation results show the performance of the scheme. This paper proposes a content clustering distribution scheme for the problems of random user distribution and limited cache. This solution uses the user’s media cloud and communication technology to complete the distribution of video content. In addition, the use of an efficient adaptive media cloud clustering mechanism and a minimized hops algorithm has enabled the reasonable deployment of 5G network caches based on the popularity of video content and user distribution. The simulation results show that the system content request response time is shortened by 50%, which effectively reduce the impact of content popularity changes on system performance. This paper analyses the important performance indicators such as cache hit rate, optimal communication radius, and maximum link access in 5G networks for multi-layer popular multimedia content distribution in response to the heterogeneity and transmission interference problems for 5G networks in 5G communications. Under the premise of noise ratio and signal-to-interference ratio threshold, related service link selection and scheduling algorithms is further proposed obtaining simulation results that approximate theoretical analysis, which effectively reduces the number of interference by 40% and improves the system throughput by 10%.

Actual Causes of Death in Relation to Media, Policy, and Funding Attention: Examining Public Health Priorities.

Despite numerous public health advancements over the last century, we continue to under-invest in prevention and public health efforts. As a result, one of the most challenging aspects of public health is prioritizing the use of limited resources. Building on the foundation of previous researchers, the goal of this exploratory study was to provide current estimates for the actual causes of death, media attention, policy focus, and research funding in the United States. In addition, we sought to calculate and compare media attention, policy attention, and research funding trends to better assess the nation's prioritization of health issues. Using a systematic approach, we searched available databases, including Media Cloud, Nexis Uni, Congress.gov, and the Department of Health and Human Services Tracking Accountability in Government Grants System from January 1, 2010-December 31, 2019 and compared how the actual causes of death in the United States align with health-related media attention, policy attention, and federal spending. Overall, our findings suggest that our priorities are not well-aligned with the actual causes of death. Certain actual causes appear to be consistently misaligned across media, legislative, and financial sectors (e.g., tobacco). This work highlights the importance of multiple strategies—media coverage, national legislation, and government spending—as indicators of public health attention and priorities. These results may inform discussions about how to best allocate U.S. public health resources to better align with the actual causes of death.

QoE-driven HAS Live Video Channel Placement in the Media Cloud

HTTP adaptive streaming (HAS) technology has been increasingly employed by video service providers (VSPs) due to its prominent benefits such as reducing interruptions of video playback and achieving higher bandwidth utilization and outstanding quality of experience (QoE). And many VSPs have deployed HAS applications in the media cloud to provide large-scale video streaming services. At present, research into the media cloud typically focuses on the management and optimization of cloud resources, such as the placement and migration of virtual machines in media cloud data centers. However, considering the HAS <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">live video streaming</i> service, existing related works have not adequately discussed the specific impact of the consumption of computing and bandwidth resources of media cloud servers on the user experience (QoE), particularly under the resource constraints in the media cloud. In this paper, we first investigate and formulate the computing and bandwidth resource consumption characteristics of HAS live video streaming with different frame rates and resolutions, and we further establish a resources-aware QoE model to quantify the user experience of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">live video channels</i> (i.e., programs). Then, based on the model, we present a QoE-driven HAS live video channel placement approach (including a placement algorithm <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HCP</i> and a rescheduling algorithm <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HCR</i> ) to optimize the channel allocation in media cloud servers, aiming to maximize the average user QoE. We abstract the maximization problem into an MMKP problem, and employ a heuristic solution to address this problem. The experimental results demonstrate the effectiveness of our proposed approach compared with benchmark solutions.

An enhanced media ciphertext-policy attribute-based encryption algorithm on media cloud

With the development of cloud computing, more and more video services are moving to the cloud. How to realize fine-grained access control of those data on cloud becomes an urgent problem. Attribute-based encryption provides a solution. However, heavy computation is still a bottleneck restricting the wider application of attribute-based encryption in cloud computing. In addition, we find that expression of the access control structure on media cloud can be further improved. To solve these problems, we propose an enhanced media ciphertext-policy attribute-based encryption algorithm and introduce its two key components, the multiple access tree and the key chain. To increase the scalability of the proposed algorithm, we discussed the issues of multi-authorization, user revocation, and 1 − n multiple access tree. Security analysis shows that enhanced media ciphertext-policy attribute-based encryption can successfully resist chosen-plaintext attacks under the decisional bilinear Diffie–Hellman assumption. Performance analysis proves both theoretically and practically that the proposed algorithm incurs less computational cost than the traditional ciphertext-policy attribute-based encryption, multi-message ciphertext-policy attribute-based encryption, and scalable ciphertext-policy attribute-based encryption by optimizing the access control structure. Our proposed algorithm has strong practical significance in media cloud.

Optimal Selection Techniques for Cloud Service Providers

Nowadays Cloud computing permeates almost every domain in Information and Communications Technology (ICT) and, increasingly, most of the action is shifting from large, dominant players toward independent, heterogeneous, private/hybrid deployments, in line with an ever wider range of business models and stakeholders. The rapid growth in the numbers and diversity of small and medium Cloud providers is bringing new challenges in the as-a-Services space. Indeed, significant hurdles for smaller Cloud service providers in being competitive with the incumbent market leaders induce some innovative players to “federate” deployments in order to pool a larger, virtually limitless, set of resources across the federation, and stand to gain in terms of economies of scale and resource usage efficiency. Several are the challenges that need to be addressed in building and managing a federated environment, that may go under the “Security”, “Interoperability”, “Versatility”, “Automatic Selection” and “Scalability” labels. The aim of this paper is to present a survey about the approaches and challenges belonging to the “Automatic Selection” category. This work provides a literature review of different approaches adopted in the “Automatic and Optimal Cloud Service Provider Selection”, also covering “Federated and Multi-Cloud” environments.

Impact of meteorological parameters on suicide mortality rates: A case-crossover analysis in Southern Germany (1990–2006)

BackgroundThere is evidence for a seasonal pattern of suicides with peaks in spring and early summer; however, only a limited number of studies has investigated whether daily changes in meteorological variables may trigger suicides. MethodsDaily fatal suicide (N = 10,595) and meteorological data were available for four Bavarian cities and ten counties (Germany) for 1990–2006. City/county-specific immediate, delayed and cumulative effects of air temperature, sunshine duration, and cloud cover on suicides were analyzed using a time-stratified case-crossover approach; city/county-specific effects were then combined using random effects meta-analysis. Potential effect modifiers were specific weather conditions, personal or regional characteristics, and season. ResultsA 5 °C increase in air temperature on the day before a suicide compared to the control days was associated with a 5.7% (95% confidence interval (CI): 0.6; 11.0) higher suicide risk. Further, the suicide risk was 6.5% (95% CI: 0.2; 13.3) higher on days with low/medium cloud cover (0–6 oktas) compared to days with high cloud cover (7–8 oktas). While daily changes in temperature were not associated with suicides in spring, we found a higher suicide risk in summer, autumn, and winter in association with temperature increases. The effects of cloud cover were strongest in summer and autumn and on days with temperature above the median (>8.8 °C). Sunshine duration was not associated with suicides. ConclusionWe found a higher risk for suicides in association with short-term increases in air temperature on the day before the event compared to the control days and on days with low to medium cloud cover. This may highlight times when people are more likely to commit suicide.

A Fine-Grained Video Encryption Service Based on the Cloud-Fog-Local Architecture for Public and Private Videos.

With the advancement of cloud computing and fog computing, more and more services and data are being moved from local servers to the fog and cloud for processing and storage. Videos are an important part of this movement. However, security issues involved in video moving have drawn wide attention. Although many video-encryption algorithms have been developed to protect local videos, these algorithms fail to solve the new problems faced on the media cloud, such as how to provide a video encryption service to devices with low computing power, how to meet the different encryption requirements for different type of videos, and how to ensure massive video encryption efficiency. To solve these three problems, we propose a cloud-fog-local video encryption framework which consists of a three-layer service model and corresponding key management strategies, a fine-grain video encryption algorithm based on the network abstract layer unit (NALU), and a massive video encryption framework based on Spark. The experiment proves that our proposed solution can meet the different encryption requirements for public videos and private videos. Moreover, in the experiment environment, our encryption algorithm for public videos reaches a speed of 1708 Mbps, and can provide a real-time encryption service for at least 42 channels of 4K-resolution videos.