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. 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. 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.
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. 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, transformed, 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.
As companies move towards digital transformation, the security of corporate digital assets is facing more and more severe challenges. How to ensure that data assets, innovative content, and other materials deposited by companies are not leaked intentionally or unintentionally during file transfer has become an urgent need for companies to solve a problem. Enterprise file transfer security risks: 1. File data errors: a large amount of data is not transmitted on time, causing data errors, and manual troubleshooting is too cumbersome. 2. Loss of hard disk: Use the form of sending and receiving hard disk to transfer large files, once the hard disk is lost, the consequences will be disastrous. 3. Information leakage: Too frequent FTP transmission methods cause the firewall to be attacked and cause information leakage. 4. File loss: Mass files cannot be completely transferred at one time, and file loss is prone to occur. Raysync, an expert in one-stop large file transfer solutions, has become the best choice for 2W+ enterprises with its high-efficiency, safe and reliable characteristics of the file transfer. Raysync data security protection: 1. AES-256 financial level encryption strength to protect user data privacy and security. 2. Added SSL security function for FTP protocol and data channel. 3. The Raysync transfer protocol only needs to open one UDP port to complete the communication, which is safer than opening a large number of firewall network ports. 4. Support the configuration of confidential certificates to make service access more secure. Raysync safety mechanism: 1. Regularly scan the CVE vulnerability risk database to resolve risky code vulnerabilities. 2. Use Valgrind/Purify for memory leak investigation during development. 3. Adopt high-performance SSL VPN encryption to provide multiple scenarios for user access security services. Raysync account security protection mechanism: 1. Adopt a two-factor strong authentication system, support USBKey, terminal hardware ID binding, and other password authentication. 2. The password saved by the user in the data is encrypted based on the AES-256+ random salt high-strength encryption algorithm, even the developer cannot recover the source password through the saved ciphertext. Raysync uses the self-developed raysync ultra-high-speed transfer protocol to build the enterprise data transfer highway in the information age, and always puts enterprise data security at the top of development, provides secure file transfer solutions for the development of enterprises, and guarantees the process of data transfer for enterprises Security and reliable.
Employees are a valuable asset of an enterprise and the cornerstone of its development. With the development of science and technology, there are more and more Internet offices, and employees can work through computers and mobile phones, which significantly improves office efficiency. At the same time, the disadvantages of Internet collaborative work are also highlighted in the process of the rapid development of enterprises. The flow of personnel is a common occurrence, but due to the popularity of Internet collaborative office, employees can obtain internal information anytime and anywhere, which poses an increasing threat to the internal information and core data of enterprises. In some resignation cases, we can see that some employees delete their own historical documents after resignation, which leads to business failure and delays work progress. In case of departing employees who steal the internal core secrets of the enterprise, take away the key technologies of the enterprise or resell information for competitors to obtain higher benefits, the enterprise will be hit hard and seriously affect the development of the enterprise. In order to protect the information security of enterprises, we have made a lot of efforts. Today, we analyze two aspects: people and information, hoping to help enterprises pay attention to the hidden dangers of information security brought by personnel mobility and protect the security of assets. Responsibility supervision Background investigation: Job seekers need background investigation, which can be carried out after both parties agree. The main purpose of the investigation is to screen out employees with bad reputation records or threats to enterprises and do preliminary prevention work. Signing Agreement: Enterprises can sign Confidentiality Agreement or Non-Competition Agreement when hiring employees, specify confidentiality content, responsible subject, confidentiality period, confidentiality obligation and liability for breach of contract, and strengthen employees' sense of responsibility. On-the-job training: Carry out "confidential knowledge training" for new employees entering the company, and create clear and comprehensive strategies to accurately outline which information, data, and documents are the property of the company, emphasize the importance of information security, clarify the consequences of data leakage, and strengthen employees' sense of confidentiality. Safe exit: Employees who leave the company are required to hand over all access rights to information and equipment to the company. In case of termination of work in HR's on-the-job employee platform, the IT department should quickly intervene and quickly cut off the equipment that may be used for authentication or allow the departing employee to connect. Similar security measures should be taken for the third-party organizations, partners, or suppliers that the company cooperates with, and quick measures are the basis for the company to avoid heavy losses. Data protection We can take responsibility for supervision for people and enterprises, and at the same time, we can also carry out protection measures for enterprises' own data and information. Permission setting: E-mail, data documents, and other forms of Internet leakage account for a large proportion of data leakage incidents. In this respect, enterprises can divide the data types, grades, and employee permissions, and manage the access, download, edit, copy, delete, and other fine settings in terms of permissions. Here, we can refer to the scientific design of identity authentication, user grouping, file outgoing monitoring, etc. File backup: In the era of big data, small groups, enterprises, companies, and large groups all produce a large amount of data in the process of development. Backup is the most direct protection for enterprises to deal with data loss and external attacks. In other words, there are traces of backup files. Security of office environment: the emergence of mobile office software is both convenient and risky for employees. For employees who carry office equipment or need to use office equipment outside the company to work, enterprises should strengthen the encryption protection of sensitive data and monitor the data flow.
In the era of big data, the production and dissemination of information are growing exponentially, and the transmission of enterprise files is facing the current situation of insecurity. Error in file data: a large amount of data is not transmitted in time, resulting in data error, and manual error checking is too cumbersome. Hard disk loss: large files are transmitted in the form of sending and receiving hard disks. Once the hard disk is lost, the consequences are unimaginable. Information leakage: Too frequent FTP transmission leads to firewall attacks and information leakage. Loss of files: massive files cannot be transmitted completely at one time, which is prone to file loss. Information security event inventory: Memcache DDoS Attack: on March 1, 2018, GitHub suffered a DDoS attack with a size of 1.35TB. in the following days, NETSCOUT Arbor reconfirmed a reflection amplification DDoS attack with a height of 1.7 Tbps caused by Memcache DDoS. Data leakage incident: A company announced that the database of a hotel was invaded, and at most about 500 million guests' information was leaked. In the same period, a special user posted that the resume information of over 200 million users in China was leaked. How to ensure the security of big data transmission. Let's take a look at how Raysync experts interpret it. Data security protection: TLS algorithm encryption, AES-256 financial grade encryption strength, protect user data privacy. Raysync protocol only needs to open one UDP port to complete communication, which is safer than opening a large number of firewall network ports. FTPS encryption technology adds SSL security function to the FTP protocol and data channel. Encrypt certificate configuration, support configuration of confidential certificates, and make service access more secure. Security mechanisms: Scan CVE vulnerability risk library regularly to solve risky code vulnerabilities. In the development process, Valgrind/Purify is used to check the memory leakage. Adopt high-performance SSL VPN encryption to provide user access security services in various scenarios. Account security protection: Adopt a double factor strong authentication system, support USBKey, terminal hardware ID binding, and other password forms for authentication. The user's password saved in the data is encrypted based on the AES-256 encryption algorithm, and even the developer can't recover the source password from the saved ciphertext. Raysync is a professional service provider of enterprise-level file transmission, and it is also the first enterprise in China to provide commercial high-performance file transmission products. Raysync provides customers with high-performance, stable, and safe data transmission services in IT, film and television, biological gene, manufacturing, and many other industries.
Raysync has superb file transfer capabilities and has served 20,000+ companies. The areas involved include government agencies, advertising media, the automobile industry, film and television production, etc. Many companies use Raysync for file transfer every day. Maybe you didn’t use Raysync directly, but maybe a movie that is currently being screened uses Raysync for accelerated transfer of video footage; maybe a medical institution is using Raysync to manage the past cases of patients...maybe each of us or More or less established contact with Raysync. The current network transfer adopts the TCP transfer protocol, which is very stable and reliable. During the transfer, the integrity of the file is the primary consideration of the TCP transfer protocol. Therefore, when the delay and packet loss occurs at the same time, it will choose to reduce Speed ensures quality. With the expansion of enterprises, the demand for transnational file transfer has soared. The longer the transfer distance, the greater the probability of delay and packet loss. Therefore, when TCP is used to transmit files transnationally, the transfer speed will decrease. In response to the bottleneck of the slow transfer speed of the TCP transfer protocol, Raysync developed its independent transfer protocol. It can also increase the packet transfer rate in the case of high delay and high packet loss. It can also control network congestion, improve transfer efficiency, and ensure that data is stable and reliable... Raysync provides enterprises with one-stop big data transfer solutions, including GB/TB/PB level large file transmission, transnational file transmission, massive small file transmission, etc. Besides, Raysync also has these features: Intelligent two-way synchronization of files; Multi-client concurrent transfer; P2P accelerated file transfer; Database disaster recovery backup; Object storage solutions; One-to-many, many-to-many heterogeneous data transfer. Since its inception, Raysync has undergone many iterations and improvements. With its excellent file transfer performance, it has become an indispensable helper for enterprises' digital transformation!
Enterprises analyze the data collected in the development process and then put into work to promote decision-making, improve efficiency, and plan the company's development direction. This means that enterprises must collect data, turn it into valuable information, and store it in a safe but still accessible location. Unfortunately, many enterprises didn't plan and manage the data in the early stage, but now they see that the data is growing and changing every day, but they are helpless. According to IDC data, enterprises are managing a large amount of data that is growing at an annual rate of 40%. Companies are not only processing more data, but the types of data are expanding. The data stream contains many unstructured data such as inventory figures, financial information, product promotional videos, promotional pictures, and so on. All these different data types need to be centralized, organized, and accessible, and usable by businesses. So, what is enterprise data management? Enterprise Data Management describes the ability of an organization to integrate, manage, protect, and distribute data from multiple data streams. This includes the ability to transmit data accurately and securely between partners and subsidiaries. Effective EDM is not easy, it can only be achieved by fully understanding your data and implementing an intelligent EDM strategy. Enterprise data management involves many parts, including: Data Governance – Data governance refers to policies and processes to ensure data integrity, quality, and security. It is a close relative of data management and covers guidelines on policy implementation, overall responsibility, and governance authority. In short, data governance establishes an organization's data laws and how, when, and by whom to enforce them. Data Integration – Enterprise data integration means moving and integrating all kinds of enterprise data into an accessible location. This is a key component that enables companies to access and use all the different data forms. Data Security – Security is an integral part of any data-related strategy. Data security usually refers to the measures taken to ensure that data are protected at all stages of its life cycle, including data at rest and data in transit. This protection involves not only anti-theft and anti-leakage measures but also the work of maintaining data integrity and preventing damage or destruction. All these factors need to be considered, and now we can draw up an enterprise data management strategy: Perform Assessment – Enterprises need to have a clear understanding of their data flows and the types of data they have in order to develop effective data management strategies. This work may be time-consuming, but it is a valuable and important process, which can help to ensure that the management methods adopted are completely matched with the data. Defining Deliverables – Data management may be a vague term. It is important for companies to outline what they hope to accomplish by implementing enterprise data management. What is the ultimate goal? How to measure success? The demand for data is sometimes overwhelmed, and some data items may be very large. In this case, the phased method of step-by-step delivery can work well. Identify Standards, Policies, and Procedures – Standards, policies, and procedures are invaluable guides to keep data where it is needed and help prevent data corruption, security breaches, and data loss. Investing in the Right People and Technology – Knowing the skills of managing data is not everyone's strong point. It is better to have in-house or consulting experts who have experience in building enterprise data management system. Their knowledge reserve can help enterprises manage data better. Similarly, it is necessary to deploy a set of excellent data transmission management software for enterprises, which can help enterprises to transmit stored data efficiently, safely, and stably.
Data collection is not comprehensive, data storage is not standardized, data interaction is not timely, and the value of data is difficult to dig. Data problems are currently faced by small and medium-sized enterprises. In the Internet era, data is growing exponentially. If enterprises hope that data can be utilized to the greatest extent, For business value, or to guide the future development direction of the company, rapid data interaction, secure storage, and comprehensive collection are essential. For many small and medium-sized enterprises with an insufficient budget for informatization, it is the easiest way to deploy software that meets the needs of enterprise informatization construction. With the help of the mature process and simple operation of the transfer software, the process of data collection, cleaning, integration, and analysis is realized. The current file transfer software has powerful file transfer performance and financial-level security. Generally, it has administrator authority control and supports third-party cloud storage, such as Raysync. The transfer speed is hundreds of times faster than FTP and HTTP. Run full bandwidth to improve file transfer efficiency; based on SSL encrypted transfer protocol, financial-grade AES-256 encrypted transfer technology to ensure data security; meticulous authority control mechanism, allowing appropriate permissions to be used by appropriate people; support third-party cloud storage platforms, Data storage safety is guaranteed. The use of these products is to take advantage of its cloud storage space and file transfer technical strength, and the enterprise itself does not need to build a computer room and set up specialized technical personnel to maintain it.
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