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5 Opinions for Big Data Transfer Security Technology
Big data transfer is becoming a new driving force for economic and social development, and is increasingly affecting economic operations, lifestyles and national governance capabilities. The security of big data movement has been improved to the level of national security. Based on the challenges and problems facing big data transfer security and the development of big data security technology, we put forward the following 5 opinions for the development of big data security technology. 5 Opinions for Big Data Transfer Security Technology 1. Build an integrated big data security defense system from the perspective of an overall security Security is a prerequisite for development. It is necessary to comprehensively improve the security of big data security technology, and then establish a comprehensive three-dimensional defense system that runs through the cloud management of big data applications to meet the needs of both countries. Big data strategy and it's market application. First, it is necessary to establish a security protection system covering the entire data life cycle, from collection to transfer, storage, processing, sharing, and final destruction. It is necessary to fully utilize data source verification, encryption of large-scale data transfer, encrypted storage in non-relational databases, privacy protection, data transaction security, prevention of data leakage, traceability, data destruction, and other technologies. The second is to enhance the security defense capabilities of the big data platform itself. It should introduce authentication for users and components, fine-grained access control, security audits for data operations, data desensitization, and other such privacy protection mechanisms. It is necessary to prevent unauthorized access to the system and data leakage while increasing attention to the inherent security risks involved in the configuration and operation of big data platform components. It is necessary to enhance the ability to respond to emergency security incidents that occur on the platform. Finally, it uses big data analysis, artificial intelligence, and other technologies to automatically identify threats, prevent risks and track attacks, and transition from passive defense to active detection. Ultimately, the goal is to enhance the security of big data from the bottom up and enhance the ability to defend against unknown threats. 2. Starting from attack defense, strengthen the security protection of big data platforms Platform security is the cornerstone of big data system security. From an earlier analysis, we can see that the nature of cyberattacks against big data platforms is changing. Enterprises are facing increasingly serious security threats and challenges. Traditional defensive surveillance methods will find it difficult to keep up with this change in the threat landscape. In the future, research on the security technology of big data transfer platforms should not only solve operational security issues but also design innovative big data platform security protection systems to adapt to the changing nature of cyber attacks. In terms of security protection technology, both open source and commercial big data platforms are in a stage of rapid development. However, the cross-platform security mechanism still has shortcomings. At the same time, the development of new technologies and new applications will reveal platform security risks that are not yet known. These unknown risks require all parties in the industry to start from the offensive and defensive aspects, invest more in the security of the big data platform, and pay close attention to the development trend of big data network attacks and defense mechanisms. It is necessary to establish a defense system suitable for and build a more secure and reliable big data platform. 3. Use key links and technologies as breakthrough points to improve the data security technology system In the big data environment, data plays a value-added role, its application environment is becoming more and more complex, and all aspects of the data life cycle are facing new security requirements. Data collection and traceability have become prominent security risks, and cross-organizational data cooperation is extensive, leading to confidentiality protection requirements that trigger multi-source aggregate computing. At present, technologies such as sensitive data identification, data leakage protection, and database security protection are relatively mature, while confidentiality protection in multi-source computing, unstructured database security protection, data security early warning, emergency response, and traceability of data leakage incidents, still relatively weak. Actively promote the development of industry-university-research integration, and accelerate the research and application of key technologies such as ciphertext calculations to improve computing efficiency. Enterprises should strengthen support for data collection, calculation, traceability, and other key links; Strengthen data security monitoring, early warning, control, and emergency response capabilities; Take data security key links and key technology research as a breakthrough; Improve the big data security technology system; To promote the healthy development of the entire big data industry. 4. Strengthen the investment in the industrialization of privacy protection core technologies, while considering the two important priorities of data use and privacy protection In the big data application environment, data usage and privacy protection will naturally conflict. Homomorphic encryption, secure multi-party computing, and anonymization technologies can strike a balance between the two and are ideal technologies to solve the privacy challenges in the application of big data. The advancement of core privacy protection technologies will inevitably greatly promote the development of big data applications. Currently, the core problem of privacy protection technology is efficiency, and its problems include high computing costs, high storage requirements, and lack of evaluation standards. Some researches, in theory, have not been widely used in engineering practice. It is very difficult to deal with privacy security threats such as multiple data sources or statistics-based attacks. In the big data environment, personal privacy protection has become a topic of much concern, and with the increasing demand for privacy protection in the future, it will drive the development and industrial application of dedicated privacy protection technologies. To improve the level of privacy protection technology in the big data environment, we must encourage enterprises and scientific research institutions to study privacy protection algorithms such as homomorphic encryption and secure multi-party computing, and at the same time promote data desensitization, audit applications, and other technical methods. 5. Pay attention to the research and development of big data security review technology and build a third-party security review system At present, the state has formulated a series of major decision-making arrangements for big data security. The government promotes the deep integration of big data and the real economy and emphasizes the need to effectively protect national data security. The National Informatization Plan puts forward an implementation plan for the big data security project. It is foreseeable that the government's supervision of big data security will be further strengthened in the future, the legislative process related to data security will be further accelerated, big data security supervision measures and technical means will be further improved, and the disciplinary work of big data security supervision will be further strengthened.
[2022] How to Improve the Security of Big Data Transfer?
Facing the challenges and threats related to the security of big data transfer, the industry has conducted targeted practices and investigations on security protection technologies. This article focuses on three aspects of the development of big data security technology: platform security, data security, and privacy protection. How to securely improve big data transfer? Technologies related to platform security, data security, and privacy protection are improving, allowing us to solve big data security issues and challenges. However, to respond to new methods of cyber attacks, protect new data applications, and meet increased privacy protection requirements, higher standards and functions will be required. Improve platform security In terms of platform technology, centralized security configuration management and security mechanism deployment can meet the security requirements of the current platform. However, vulnerability scanning and attack monitoring technologies for big data platforms are relatively weak. In terms of technologies for defending platforms from network attacks, current big data platforms still use traditional network security measures to defend against attacks. This is not enough for the big data environment. In the big data environment, the extensible defense boundary is vulnerable to attack methods that cover up the intrusion. Besides, the industry pays little attention to potential attack methods that may come from the big data platform itself. Once new vulnerabilities appear, the scope of the attack will be huge. Improve data security In terms of data security, data security monitoring and anti-sabotage technologies are relatively mature, but data sharing security, unstructured database security protection, and data violation traceability technologies need to be improved. Currently, there are technical solutions for data leakage: technology can automatically identify sensitive data to prevent leakage; The introduction of artificial intelligence and machine learning makes the prevention of violations move toward intelligence; The development of database protection technology also provides a powerful way to prevent data leakage guarantee. The ciphertext calculation technology and the data leakage tracking technology have not yet been developed to the extent, which they can meet the needs of practical applications, and it is still difficult to solve the confidentiality assurance problem of data processing and the problems related to tracking data flow. Specifically, the ciphertext calculation technology is still in the theoretical stage, and the calculation efficiency does not meet the requirements of practical applications. Digital watermarking technology cannot meet the needs of large-scale and fast-updated big data applications. Data lineage tracking technology requires further application testing and has not yet reached the mature stage of industrial applications. Digital watermarking technology cannot meet the needs of large-scale and fast-updated big data applications. Data lineage tracking technology requires further application testing and has not yet reached the mature stage of industrial applications. Digital watermarking technology cannot meet the needs of large-scale and fast-updated big data applications. Data lineage tracking technology requires further application testing and has not yet reached the mature stage of industrial applications. Improve privacy security In terms of privacy protection, technological development clearly cannot meet the urgent need for privacy protection. The protection of personal information requires the establishment of a guarantee system based on legal, technical, and economic methods. Currently, the widespread use of data desensitization technology poses challenges to multi-source data aggregation and may lead to failure. So far, there are few practical application case studies for emerging technologies such as anonymization algorithms, and there are other common problems with this technology, such as low computational efficiency and high overhead. In terms of computing, continuous improvement is needed to meet the requirements of protecting privacy in a big data environment. As mentioned earlier, the conflict between big data applications and personal information protection is not just a technical issue. Without technical barriers, privacy protection still requires legislation, strong law enforcement, and regulations to collect personal information for big data applications. Establish a personal information protection system that includes government supervision, corporate responsibility, social supervision, and self-discipline of netizens.
3 Challenges Faced by Big Data Transfer Technology
The ability to effectively use big data to gain value comes down to the ability of organizations to run analytical applications on the data, usually in the data lake. Assume that the challenges of capacity, speed, diversity, and accuracy are solved-measuring data readiness. The data is ready to pave the way for predictive analysis. Data readiness is built on the quality of the big data infrastructure used to support business and data science analysis applications. For example, any modern IT infrastructure must support data migration associated with technology upgrades, integrated systems, and applications, and can transform data into required formats and reliably integrate data into a data lake or enterprise data warehouse ability. 3 Challenges Faced by Big Data Transfer Technology Three big challenges facing big data technology, so why do so many big data infrastructures collapse early in the implementation life cycle? All this goes back to the last of McKinsey’s big data offer in 2011: “As long as the right policies and driving factors are formulated”. Some reasons why big data projects cannot be started are as follows: 1. Lack of skills Despite the increase in machine learning, artificial intelligence, and applications that can run without humans, the imagination to drive big data projects and queries is still a data scientist. These "promoters" referred to by McKinsey represent skills that are in great demand on the market and are therefore rare. Big data technology continues to affect the recruitment market. In many cases, big data developers, engineers, and data scientists are all on-the-job, learning processes. Many high-tech companies are paying more and more attention to creating and training more data-related positions to use the principles of big data. It is estimated that by 2020, 2.7 million people will be engaged in data-related jobs, and 700,000 of them will be dedicated to big data science and analysis positions to highly competitive and expensive employees. 2. Cost The value of the big data analytics industry is nearly $125 billion, and it is only expected to grow. For big data implementation projects, this means expensive costs, including installation fees and regular subscription fees. Even with the advancement of technology and the reduction of barriers to entry, the initial cost of big data may make the project impossible. Investment may require traditional consulting, outsourcing analysis, internal staffing, and storage and analysis software tools and applications. Various cost models are either too expensive, or provide the functionality of the minimum viable product, and cannot provide any actual results. But first, a company that wants to properly implement big data must prioritize architecture and infrastructure. 3. Data integration and data ingestion Before performing big data analysis, data integration must be performed first, which means that various data need to be sourced, moved, transferred, and provisioned into big data storage applications using technologies that ensure security. Control during the entire process. Modern integration technologies that connect systems, applications, and cloud technologies can help organizations produce reliable data gateways to overcome data movement problems. Companies striving to modernize their systems and deploy strategies to integrate data from various sources should tend to adopt a B2B-led integration strategy that ultimately drives the development of partner ecosystems, applications, data storage, and big data analysis platforms To provide better business value.
What is the Big Data Transfer You Need to Know?
Nowadays, a large amount of analog and digital data is transmitted between global commercial networks in the form of data transfer. What is data transfer? Data transfer,is the transfer of data from one digital device to another digital device. This transfer takes place through point-to-point data streams or channels. These channels may have been in the form of copper wires before, but are now more likely to become part of the wireless network. As we all know, data transfer methods can refer to digital data, and the effectiveness of data transfer depends to a large extent on the amplitude and transfer speed of the carrier channel. The amount of data transferred in a given period is the data transfer rate, which specifies whether the network can be used for tasks that require complex data-intensive applications. Network congestion, delays, server health, and insufficient infrastructure can cause data transfer rates to be lower than standard levels, thereby affecting overall business performance. High-speed data transfer rates are essential for handling complex tasks such as online streaming and large file transfers. The importance of content delivery networks in data transfer High-quality delivery of websites and applications to as many locations around the world requires infrastructure and expertise to achieve low-latency, high-performance reliability, and high-speed data transfer delivery. Professional content delivery networks provide multiple advantages, including seamless and secure distribution of content to end-users, no matter where they are. The content delivery network uses complex node systems strategically located around the world to deliver content through more efficient use of network resources, thereby reducing the load on the enterprise's central server. Higher data rate conversion can improve user experience and increase reliability. By using intelligent routing and adaptive measures to find the best and most successful path in the case of network congestion, bottlenecks can be avoided-indicating that the amount of data flowing into network resources is too much to be processed. Faster data transfer FTP and HTTP are common methods of the file transfer. For example, FTP can be used to transfer files or access online software archives. HTTP is a protocol used to indicate how messages are defined and transmitted. It also determines the actions taken by web browsers and servers in response to various commands. HTTP requests are identified as stateless protocols, which means they have no information about previous requests. ISPs provide a limited level of bandwidth for sending and receiving data communications, which can lead to excessive slowdowns that enterprises cannot afford. As Raysync big data transfer, small file transfer is more than 5,000 per second, and millions of files can be listed in 5 minutes. The same file-second transfer speed can reach 20,000 per second, which is more than 100 times faster than traditional FTP.
12 Best Ways to Share Big Files in 2022
If you just recorded a home video or created the final hybrid tape , then you will undoubtedly be eager to share it with your friends and family. Depending on the size and number of files you need to send, this may be a problem. For example, Gmail only allows you to attach files up to 25MB to emails. Not to mention the fact that large files lurking in the "Sent" folder will quickly take up your storage space quota! If you need to send large files online, there are many good ways to avoid trouble. We highlight the 12 best files transfer methods, most of which are free . Use a VPN What is the relationship between VPN and sharing large files? Some Internet service providers use broadband traffic management to regulate upload bandwidth . Using a VPN as our first choice ExpressVPN means that your ISP cannot determine the type of file you are uploading, so in theory, traffic shaping cannot be applied to your account. Use specialized services The new generation of file transfer service is browser-based and has built-in proprietary technology to accelerate the upload of large files. Raysync is one of them and specializes in transferring large files via the cloud. But the advantages are clear: Raysync is faster, more secure and more efficient than other transfer methods. In addition, Raysync offers a free trial opportunity. Use file compression One of the easiest ways to solve the problem of sending large files is to use file compression software, such as the cross-platform program 7-Zip. This is especially convenient if you have multiple files because you can put them in a folder and then compress them all at once. 7-Zip is suitable for Windows, Mac, and Linux, and can compress files into regular ZIP format, and it's slightly more efficient than 7ZIP. Most major operating systems can extract ZIP files without any other software. 7-Zip also allows you to set a password to protect the files, so you can share them safely. Please keep in mind that although uploading very large files may time out. Express 20TB external hard drive The fastest way to transfer massive large files is not via the Internet, but to use disk drives and messengers. All large cloud providers can use hard drives to transfer large amounts of data. Microsoft Azure charges a nominal fixed fee, which means that it costs approximately US$75 per storage device, but you must be prepared to provide your drives. This is similar to Amazon Web Services' import/export disk, while Google uses a third party. The WD My Book Duo external hard drive is priced at $749.99 and has a capacity of 20TB , making it the largest and most cost-effective device in its class. On a consumer-grade broadband line, it will take more than 500 hours to transmit the contents of a 20TB external hard drive on a 100Mb dedicated line, and it is expected to last more than a month and is only used for uploading. Remember to keep a copy of the file and encrypt the hard drive to be sent. 5. Google Drive Although Gmail messages can only contain attachments up to 25MB, when the file is too large, Google can give you the option to place it in Google Drive and send a link for sharing. Gmail users can share files and folders up to 10GB. Considering that Google's free tier can provide you with 15GB of storage space, so you can share large files repeatedly for absolutely free . Google allows you to choose to create a link that can be shared with anyone or just to create a link to the person who sent you an email with the link. 6. FTP Although FTP may be outdated compared to cloud services such as Dropbox and Google Drive, it is still one of the most reliable methods for uploading and downloading files. All operating systems support FTP, and many websites and add-ons support uploading and downloading from your browser, such as FireFTP. Windows and Mac users can also use the free desktop FTP client Cyber duck. The only disadvantage is that you need to have access to remote servers . Many companies like DriveHQ provide some free storage space , and the price is comparable to cloud storage providers. 7. Mediafire True to its name, MediaFire is a pioneer. Sign up for a free account and you will get 10GB of storage space. Connect your Facebook and Twitter accounts, install mobile apps, and refer friends to get up to 40GB of bonus space. You can upload files directly from your computer or the web and generate a link that will allow others to download the file from the MediaFire website. The paid subscription costs US$3.75 per month and includes 1TB of storage space, a 20GB file size limit, and the elimination of annoying verification codes and advertisements. Another convenient advanced feature is a one-time link, which ensures that once the recipient downloads the files, they can no longer be accessed. 8. Hightail Hightail has considered the needs of business users. After registration, you can create special "spaces" for various files and projects, which can then be shared with others. The convenient "PipPoints" function can even be used to take notes on documents while you and others are working on them. The free Lite version of Hightail only allows files up to 100MB to be shared. The Pro subscription is priced at US$12 per month, which includes unlimited workspace and supports files up to 25GB. There is also no limit to the number of people who can access a file at any given time. 9. WeTransfer WeTransfer is one of the simplest services for sharing large files. With just a few clicks, the website will automatically send you the files, which can be downloaded for 7 days. Everything is also very user-friendly, with a step-by-step wizard to guide you through the upload process. You can transfer up to 2GB on a free account, but for US$12 per month or US$120 per year , you can upgrade to WeTransfer Plus, which can transfer up to 20GB of files at a time, and 1TB Storage. Besides, you can choose to set a password to download the file-in addition, and customize the background and email as needed. 10. Resilio synchronization This handy tool used to be BitTorrent Sync, which uses the BitTorrent protocol and can directly synchronize files between devices. This peer-to-peer connection can be used for two or more devices, such as phones and desktop PCs. Resilio Sync also supports generating secure links to allow your contacts to download files from your folder. This naturally means that your device must be online at the time to be accessible. The software itself is provided for free, and there is no limit to how much data you can transfer or store. Note: Only "Personal Sync" is free. Sync Home adds more features and is priced at US$60 , while Sync for Family can accommodate up to 5 family members and retails for US$100 . 11. Send Anywhere Send Anywhere is suitable for almost every platform you can think of and can transfer files up to 10GB completely free. Which is suitable for Windows, macOS, Linux and Amazon Kindle, as well as plugins for WordPress and Outlook. The browser widget allows you to share files up to 10GB, but the paid service allows you to share files without restrictions. 12. Dropbox Sign up for this cloud storage service and you can share all files moved into the Dropbox folder using a web link. Some operating systems allow you to do this by right-clicking, while other operating systems may require you to log in to the site and click the "share" link. Most importantly, the person you send the link to does not have to be a Dropbox user-they just need to download the file from the site. Dropbox has a free tier that gives you 2GB of storage space, but you can earn more by referring friends to use the service-or by signing up for Dropbox Plus for $9.99 a month to increase the limit to 2TB. The latter also allows you to better control files, including version control and remote device wipe and can set download passwords. Conclusion To find a flexible solution with security and speed, cloud storage is the only way to go. Cloud solutions such as Raysync, Google Drive, Dropbox, and the like provide amazingly flexible pricing and even free storage.
[3 Ways] Big Data Encrypted Transmission Methods
1. MQTT data encryption transfer algorithm An improved MQTT protocol data transfer encryption algorithm MQTT-EA is proposed. In this algorithm, the IoT device side and the server-side randomly generate their private keys, then notify each other of their private keys and combine them into the final session master key through the algorithm, which is encrypted and decrypted by DES to transmit secure data. The attack on the data transfer process by adversaries A and B is simulated, and it is verified that MQTT-EA is safe under the premise that the session key generation algorithm is not leaked. 2. Summary of key protocols and application scenarios of time-sensitive networks With the development of information technology, there is an increasing demand for scenarios where things and things are the main body of communication, such as factory automation control, automatic driving, etc. The requirements for data transfer delay of this type of communication far exceed the controllable range of traditional Ethernet. , The time-sensitive network came into being. Time-sensitive networks are based on standard Ethernet, providing standardized technologies for deterministic information transfer, minimizing jitter through time-aware scheduling mechanisms, and providing reliable data transfer guarantees for time-sensitive applications. Through the description of relevant international standards for time-sensitive networks, the core features and mechanisms are introduced, and application scenarios such as in-vehicle networks, industrial Internet, avionics networks, and mobile fronthaul networks are analyzed and researched. 3. Design of LoRa's Remote Distributed Agricultural Environment Monitoring System To solve the problems of complex networking of traditional Internet of Things, short transfer distance, and high power consumption, and agricultural environment monitoring system based on LoRa technology is proposed. The system uses the peripheral functions of the STM32 microcontroller to drive the sensors to monitor a variety of environmental data and uses the LoRa wireless communication module to build a data transfer network. The summary node in the data transfer network receives all the data transmitted from the monitoring node, then packs the data and uploads it to the server through the General Packet Radio Service communication network. The upper computer developed by the C language can realize the monitoring data Real-time display and save. After testing, the system can accurately monitor agricultural environmental data in real-time, is stable and reliable, and can meet the needs of agricultural environmental monitoring.
Everything We Need to Know About Data Movement
Data movement is exactly what it sounds like: moving data from one place to another. We rely on various channels to communicate online, so we leave too much data behind, including data, files, etc. These become our important assets, so data to be moved is very important. In this article, we will analyze the definition of moving data, risks and challenges, and introduce some common data movement solutions. What's data movement? Data movement, is the ability to move data from one location to another within an organization using techniques, such as Extract, Transform, Load, Extract, Load, Transform , Data Replication, and Change Data Capture , Its purpose is mainly for data migration and data warehousing. The principle and importance of moving data In generally, the are two ways: replication and synchronization. Replication Provides a reliable and cost-effective way to create an accurate and up-to-date copy of your data from one or more sources that can be made available to anyone who needs access to it, no matter when or where they work. You can maintain control of the replicated database with flexible configurations for archiving and retention rules, data movement and breathing, and storage. Your data remains available for use in the original application or with analytics tools installed. Synchronization Keep replicated data up to date so users and applications have the best information available when working with it. You can update the replicated database in a batch or live configuration. For many relational databases, you can use the Change Data Capture feature to instantly synchronize new data. What are the risks and challenges of data movement? Because data is so valuable, it’s important to carefully plan and execute its migration. Issues during data movement can corrupt data, causing errors and inefficiency when it finally reaches its destination. Data Security Security is another common concern when dealing with data, especially for organizations that handle sensitive personal information like addresses, medical history, and the like. Make sure you take the necessary steps to ensure a secure data transfer. For an online movement, that could mean data encryption. Data Loss Risk During the data migration process, data loss can occur. When the data is migrated to the new system or target system, some of the data may not migrate over from the source system. Extended Downtime Risk The risk of extended downtime comes when the data migration process takes longer than expected. During the migration process, the source system is not active, so this poses potential risks for organizations and stakeholders. Capacity Issues Some businesses also run into trouble if they try to fit in data migration on top of their regular day-to-day work. Data migration can seem straightforward, but it’s still a very important undertaking that needs to be taken seriously. Methods of data movement Xplenty Xplenty is a cloud-based data integration platform. It is a complete toolkit for building data pipelines. It provides solutions for marketing, sales, customer support, and developers. These solutions are available for the retail, hospitality, and advertising industries. Xplenty is an elastic and scalable platform. Raysync Raysync is a software-based file transfer solution for accelerating the transfer process and improving the work efficiency of enterprises. Raysync provides fast file transfer solutions that are perfect alternatives to FTP. By adopting the patented UDP protocol, Raysync delivers your data faster and won't over-burden your network. Our solutions enable you to send files of any size or format at full line speed, hundreds of times faster than FTP while ensuring secure and reliable delivery. Rsync Rsync is a data migration tool for transferring data across computer systems efficiently. It migrates data based on the timestamp and file size. Configero Data Loader Configero’s Data Loader for Salesforce is a web-based data loader application. It speeds up the activities of inserting, updating, and deleting Salesforce data. It has much-improved error handling as errors are displayed in the grid, thereby allowing direct editing of errors. Azure DocumentDB Azure Document DB Data Migration Tool is owned by Microsoft. It is an excellent tool to be used for data movement from various data sources into Azure Document DB. HDS Universal Replicator Hitachi Universal Replicator software provides enterprise-level storage system replication while delivering business continuity at the same time. It is capable of working with heterogeneous operating systems. Best Choice---Fast, Secure, and Reliable Data Movement Tool With its high-speed transfer protocol, Raysync provides all-around support for enterprises in large file interactions and cross-platform cooperation, achieving standardization within and between enterprises. While Raysync has been continuously improving its file transfer acceleration technology, it also embraces the objectives of solving enterprise file transfer management into its scope of service to a full extent, building a smart file transfer system: Data Synchronization Supports two-way file synchronization that maintains the consistency of data across multiple devices, ensuring no redundant fragmented files are produced and multi-point data sync is efficient. Point-to-point Transfer Adopts user ID to achieve point-to-point transfer, eliminating intermediate transfer for rapid file-sharing. Standard Bank-Level Encryption Technology With the AES-256+SSL+Random salt high-density encryption algorithm, even the developers are unable to recover the root password through the stored ciphertext, making sure the data security is worry-free. Audit Trails Uses transfer logs and operations logs to supervise user behavior, easily trace all operations and file content, effectively control improper usage behavior and help enterprises to achieve better file management. User-defined Management User-defined management perfectly plots out the organizational structure, supporting group management by defining regions, departments, and role-based permissions that set authority to standardize enterprise users' operation. Intelligence Nodes Management With intelligence nodes management equipped, it supports unified management of all node machines in both the internal and external network environment to monitor and collect all operation logs and data synchronously. Hybrid Cloud Storage Raysync supports more than 10 mainstream storage methods including hybrid storage effectively to assist enterprises to store, backup, migrate and synchronize their files in an orderly manner. Conclusion As a one-stop solution provider, Raysync has independently developed its core transfer technology with its professional technical teams to offer high-performance, secure, and reliable large file transfer and file management services for major enterprises.
Interview with Hasan Köroğlu, Founder of Kadraj Group, the Biggest Digital Delivery Hub for Turkish Dramas
Hasan Köroğlu is the founder of Kadraj Group. His knowledge and experience on the Internet and audio visual technologies as a producer for many years had Kadraj growing fast. Kadraj is the leading company on QC, localization, and delivery services in Turkey, which was established by Hasan in February 2019. It has been 12 years and 8 months until now. It was just a decade ago when Turkish dramas became popular all over the world, just after two years later Kadraj was established. It was perfect timing for their services, and they are working together with the major market actor including producers, distributors, and broadcasters over these years. Today they are the pioneer in this market, in their domain. Here’s the interview between Hasan Köroğlu and Raysync, in which Hasan shared his use case in data delivery and the difficulties his team met in the daily workflow. Raysync: Hi Hasan! Could you please describe your use case in worldwide content delivery? Hasan: Kadraj is the biggest digital delivery hub for Turkish dramas and Turkish series. Keeping in mind the demand for Turkish dramas on the world market that makes our position unique. After the latest progress on internet technologies and almost 95% of the deliveries are completed via internet, just make it clear, we are talking about deliveries of thousands of hours of content every month to over 40 countries and around 150 clients/broadcasters all over the world. This is why we need alternatives all the time and we are pushing the boundaries all the time. Raysync: What difficulties have your team met in the workflow? And how does Raysync helps to solve? Hasan: Especially creating new accounts and user permissions, user management - they are major problems. And there were some issues with the stability of the platforms we were using back then, also bandwidth management was another big problem for us. Raysync solved almost all of them, especially the bandwidth management is really important for us and Raysync did it. We are glad. Raysync: What projects did Raysync handle the data transfer for? Hasan: Hundreds of Turkey series and we have sent over 200 thousands of unique commercial hours of TV content. For the last 10 years, the TV content that has been exported to other countries from Turkey, has been prepared and delivered by Kadraj, by us. Projects Kadraj Participated Raysync: How big the file is for each transfer? Hasan: Let's say it's between 20 gigabytes to one terabytes for each file. May because let’s say a 45 minutes episode is around 20 gigabytes in MXF format, and Turkey series are around two hours long and two hours long 4k raw content is more than a terabyte, those are single files. We have over six petabytes data at the office right now. But keep in mind this is not a big data, this is a volumetric data. We do not have that much files, but the files are really big. Raysync: How do you like Raysync’s data transfer and acceleration services? Hasan: Actually, this is something we really haven't thought about it, because just after implementing the software, the platform into our workflow, we got used it very quickly and feel like we haven't migrated but we were using it from the very beginning. It's really easy, we did like it very much. Because it's easy and it's obviously planned and developed with really experienced people, they know what they're doing. Raysync: What's next plan with Kadraj? Hasan: There are lots of plans. For the last couple of months we are working on ISO 27001 certification and we are in the process of TPN assessment. And this is why we are updating our structure, everything at the office, so there will be lots of changes in the coming a few months, maybe before the new year and a lot will change at Kadraj. Special thanks to Hasan Köroğlu from Kadraj Group.

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