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  • How much is the annual income of a machine learning engineer? Introducing annual income situation and salary increase method

    How much is the annual income of a machine learning engineer? Introducing annual income situation and salary increase method

    Annual income of a machine learning engineer?

    Machine learning is used in many places and is one of the technologies that enrich our lives. Along with that, attention is also focused on machine learning engineers who build machine learning. What I am concerned about is the outline of machine learning engineers and the annual income situation. This time, we will introduce the outline of machine learning engineers and the annual income situation.

     

    What kind of profession is a machine learning engineer?


    Due to the rapid development of AI technology and the promotion of digital transformation by companies, the attention of machine learning engineers is increasing. So, first, I will explain about machine learning engineers.

    What is a machine learning engineer?

    A machine learning engineer is a job that specializes in machine learning technology in AI development. Machine learning is one of the technologies required to realize AI, and derives certain rules and rules based on a large amount of data. Machine learning engineers use their knowledge of statistics and mathematics to build machine learning models in order to find certain regularities from large amounts of data.

     

    Job description of a machine learning engineer

    Machine learning engineers are mainly responsible for data analysis, construction, and construction and verification of machine learning models. In particular, building and verifying machine learning models is the most important task. In machine learning, the accumulated data is learned according to the constructed machine learning model. At this time, the learning result makes a big difference depending on the machine learning model selected. Therefore, it is necessary to modify the machine learning model with higher accuracy by repeating the verification.

     

    Differences between AI engineers and data scientists

    Similar occupations to machine learning engineers include AI engineers and data scientists. Since AI engineer is a term that refers to all engineers involved in AI, machine learning engineers are also included in AI engineers. However, some companies make a clear distinction between AI engineers and machine learning engineers. A data scientist is a job that is treated in much the same way as a machine learning engineer when looking at the work content. However, some companies make a clear distinction, so it is necessary to confirm in advance.

     

    Check the annual income of machine learning engineers


    Next, let’s take a look at the annual income of machine learning engineers.

    Domestic average annual income

    According to data from the job search site Indeed, the average annual income of machine learning engineers in Japan is around 6.3 million yen. According to the site, the average annual salary of a general engineer is about 4-5 million yen, so it can be said that machine learning engineers have a high salary level. In recent years, the Ministry of Economy, Trade and Industry has been promoting digital transformation, and the importance of AI is increasing in society as a whole. Therefore, increasing demand is increasing the number of companies offering higher salaries.

     

    Trends in average annual income overseas

    Overseas machine learning engineers are often offered higher annual salaries than domestic ones. According to the data of the American recruiting site “Glassdoor”, the average annual income of machine learning engineers is about 14 million yen. If you are a machine learning engineer and want to achieve a high annual income, it is recommended that you also consider working overseas. However, the level required is likely to be higher than in Japan, so you must improve your skills on a daily basis.

     

    To aim to increase annual income as a machine learning engineer


    In order to increase your annual income as a machine learning engineer, the following points are important.

    • Catch up on the latest technology
    • Learn a programming language
    • Improve project management skills
    • Improve your English
    • Consider changing jobs

     

    Catch up on the latest technology

    As technology advances rapidly in the IT industry, it is important to keep an antenna on and catch up with the latest technology and knowledge. In particular, new information is being transmitted one after another in advanced technologies such as machine learning and AI. There are few human resources who can handle the latest technology and the demand is high, so if you do not miss the catch-up, you will be a valuable human resource.

     

    Learn a programming language

    In order to realize machine learning, it is necessary to code “Python” and “R language”. Therefore, you must acquire the knowledge to code each one. Also, when implementing machine learning, knowledge of specialized libraries and frameworks is also required, so it is good to remember the commonly used “NumPy, Pandas, Tensorflow, Matplotlib” and so on.

     

    Improve project management skills

    If you want to advance your career as an engineer, it is important to improve your project management skills in addition to technology skills. If you gain some experience as an engineer, you will have more opportunities to play an active role not only in the field but also as a team leader. In addition to managing the team, there is a wide range of tasks such as formulating development policies and selecting technologies for solving problems. Managers tend to have higher annual incomes, so think ahead and improve your management skills.

     

    Improve your English

    The fields of machine learning and AI are more advanced overseas than in Japan. Therefore, you have to read foreign documents to get the latest knowledge. At that time, it is important to acquire English proficiency so that you can read overseas documents. By acquiring the latest information, even domestic companies will be able to become valuable human resources.

     

    Consider changing jobs

    After gaining experience as a machine learning engineer, it is a good idea to move to a company with better conditions. Due to the high demand for machine learning engineers themselves, it is possible that you will find a company that will generate a higher annual income for the same job. Furthermore, if you are confident in your language skills such as English, it is also effective to work overseas such as the United States in search of a high income.

     

    To get a satisfying annual income with a machine learning engineer


    The following points are important for a machine learning engineer to earn a satisfactory annual income.

    • Choose a job-based employment company
    • Choose a company that is willing to invest in education
    • Check the personnel evaluation system

    Choose a job-based employment company

    Job-type employment is employment that emphasizes external competitiveness and determines salary based on market value. Since job-based employment focuses on skills and determines salary, it is likely that the salary will be higher than the seniority-based assessment found in many companies.

     

    Choose a company that is willing to invest in education

    It is important for engineers to constantly study and improve their skills. Therefore, by selecting a company with a well-educated environment, you can work while increasing your own market value. Also, a company that is willing to invest in education is a company that understands the value of engineers, so it is highly likely that it will get a proper evaluation. By increasing the market value, you can expect high annual income even when you change jobs.

     

    Check the personnel evaluation system

    In order to obtain a satisfactory annual income, it is important to have an evaluation system that clearly and properly evaluates your contribution. Many companies often carry out personnel evaluations in seniority order. However, in seniority, there is almost no such thing as a sudden promotion or salary increase due to evaluation. Therefore, it is important that the evaluation system only properly evaluates ability.

     

    If you want to touch machine learning, leave it to TRYING

    To become a machine learning engineer, you must acquire knowledge and skills related to machine learning. However, it is difficult to learn machine learning from scratch. Therefore, I would like to recommend two cloud-based business efficiency improvement tools developed by TRYING.

     

    Experience machine learning with the no-code AI tool “UMWELT.”

    UMWELT is a tool that can use AI without programming. There is no need to prepare a special environment for using AI in-house, and AI can be used while minimizing preparation costs such as costs and man-hours. It is equipped with a large number of AI algorithms that help improve work efficiency, and anyone can easily build an AI system by freely combining these algorithms.

     

    Easy automatic shift creation with AI cloud “HR BEST”

    HRBEST is a tool that automates complex shift creation with “combinatorial optimization” technology. Since shifts can be created according to the Labor Standards Law and industry rules, shift creation work for managers, who tend to be personalized, can be easily automated. Since it is a cloud service, it is always possible to respond to sudden shift changes and law revisions, and always keep the latest shift status.

     

    summary

    Machine learning engineers have a higher average annual income than general engineers, and it is expected that the level will continue to rise in the future. Many companies would like to acquire machine learning engineers to improve work efficiency and create businesses. However, it is difficult to hire machine learning engineers, and many companies may be worried that they will not be able to incorporate machine learning.  UMWELT / HRBEST is an AI tool that can be used without the need for an instrument learning engineer. Please take this article as an opportunity to contact TRYING.

     

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  • How much is the annual income of a machine learning engineer? Introducing annual income situation and salary increase method

    How much is the annual income of a machine learning engineer? Introducing annual income situation and salary increase method

    Annual income of a machine learning engineer?

    Machine learning is used in many places and is one of the technologies that enrich our lives. Along with that, attention is also focused on machine learning engineers who build machine learning. What I am concerned about is the outline of machine learning engineers and the annual income situation. This time, we will introduce the outline of machine learning engineers and the annual income situation.

     

    What kind of profession is a machine learning engineer?


    Due to the rapid development of AI technology and the promotion of digital transformation by companies, the attention of machine learning engineers is increasing. So, first, I will explain about machine learning engineers.

    What is a machine learning engineer?

    A machine learning engineer is a job that specializes in machine learning technology in AI development. Machine learning is one of the technologies required to realize AI, and derives certain rules and rules based on a large amount of data. Machine learning engineers use their knowledge of statistics and mathematics to build machine learning models in order to find certain regularities from large amounts of data.

     

    Job description of a machine learning engineer

    Machine learning engineers are mainly responsible for data analysis, construction, and construction and verification of machine learning models. In particular, building and verifying machine learning models is the most important task. In machine learning, the accumulated data is learned according to the constructed machine learning model. At this time, the learning result makes a big difference depending on the machine learning model selected. Therefore, it is necessary to modify the machine learning model with higher accuracy by repeating the verification.

     

    Differences between AI engineers and data scientists

    Similar occupations to machine learning engineers include AI engineers and data scientists. Since AI engineer is a term that refers to all engineers involved in AI, machine learning engineers are also included in AI engineers. However, some companies make a clear distinction between AI engineers and machine learning engineers. A data scientist is a job that is treated in much the same way as a machine learning engineer when looking at the work content. However, some companies make a clear distinction, so it is necessary to confirm in advance.

     

    Check the annual income of machine learning engineers


    Next, let’s take a look at the annual income of machine learning engineers.

    Domestic average annual income

    According to data from the job search site Indeed, the average annual income of machine learning engineers in Japan is around 6.3 million yen. According to the site, the average annual salary of a general engineer is about 4-5 million yen, so it can be said that machine learning engineers have a high salary level. In recent years, the Ministry of Economy, Trade and Industry has been promoting digital transformation, and the importance of AI is increasing in society as a whole. Therefore, increasing demand is increasing the number of companies offering higher salaries.

     

    Trends in average annual income overseas

    Overseas machine learning engineers are often offered higher annual salaries than domestic ones. According to the data of the American recruiting site “Glassdoor”, the average annual income of machine learning engineers is about 14 million yen. If you are a machine learning engineer and want to achieve a high annual income, it is recommended that you also consider working overseas. However, the level required is likely to be higher than in Japan, so you must improve your skills on a daily basis.

     

    To aim to increase annual income as a machine learning engineer


    In order to increase your annual income as a machine learning engineer, the following points are important.

    • Catch up on the latest technology
    • Learn a programming language
    • Improve project management skills
    • Improve your English
    • Consider changing jobs

     

    Catch up on the latest technology

    As technology advances rapidly in the IT industry, it is important to keep an antenna on and catch up with the latest technology and knowledge. In particular, new information is being transmitted one after another in advanced technologies such as machine learning and AI. There are few human resources who can handle the latest technology and the demand is high, so if you do not miss the catch-up, you will be a valuable human resource.

     

    Learn a programming language

    In order to realize machine learning, it is necessary to code “Python” and “R language”. Therefore, you must acquire the knowledge to code each one. Also, when implementing machine learning, knowledge of specialized libraries and frameworks is also required, so it is good to remember the commonly used “NumPy, Pandas, Tensorflow, Matplotlib” and so on.

     

    Improve project management skills

    If you want to advance your career as an engineer, it is important to improve your project management skills in addition to technology skills. If you gain some experience as an engineer, you will have more opportunities to play an active role not only in the field but also as a team leader. In addition to managing the team, there is a wide range of tasks such as formulating development policies and selecting technologies for solving problems. Managers tend to have higher annual incomes, so think ahead and improve your management skills.

     

    Improve your English

    The fields of machine learning and AI are more advanced overseas than in Japan. Therefore, you have to read foreign documents to get the latest knowledge. At that time, it is important to acquire English proficiency so that you can read overseas documents. By acquiring the latest information, even domestic companies will be able to become valuable human resources.

     

    Consider changing jobs

    After gaining experience as a machine learning engineer, it is a good idea to move to a company with better conditions. Due to the high demand for machine learning engineers themselves, it is possible that you will find a company that will generate a higher annual income for the same job. Furthermore, if you are confident in your language skills such as English, it is also effective to work overseas such as the United States in search of a high income.

     

    To get a satisfying annual income with a machine learning engineer


    The following points are important for a machine learning engineer to earn a satisfactory annual income.

    • Choose a job-based employment company
    • Choose a company that is willing to invest in education
    • Check the personnel evaluation system

    Choose a job-based employment company

    Job-type employment is employment that emphasizes external competitiveness and determines salary based on market value. Since job-based employment focuses on skills and determines salary, it is likely that the salary will be higher than the seniority-based assessment found in many companies.

     

    Choose a company that is willing to invest in education

    It is important for engineers to constantly study and improve their skills. Therefore, by selecting a company with a well-educated environment, you can work while increasing your own market value. Also, a company that is willing to invest in education is a company that understands the value of engineers, so it is highly likely that it will get a proper evaluation. By increasing the market value, you can expect high annual income even when you change jobs.

     

    Check the personnel evaluation system

    In order to obtain a satisfactory annual income, it is important to have an evaluation system that clearly and properly evaluates your contribution. Many companies often carry out personnel evaluations in seniority order. However, in seniority, there is almost no such thing as a sudden promotion or salary increase due to evaluation. Therefore, it is important that the evaluation system only properly evaluates ability.

     

    If you want to touch machine learning, leave it to TRYING

    To become a machine learning engineer, you must acquire knowledge and skills related to machine learning. However, it is difficult to learn machine learning from scratch. Therefore, I would like to recommend two cloud-based business efficiency improvement tools developed by TRYING.

     

    Experience machine learning with the no-code AI tool “UMWELT.”

    UMWELT is a tool that can use AI without programming. There is no need to prepare a special environment for using AI in-house, and AI can be used while minimizing preparation costs such as costs and man-hours. It is equipped with a large number of AI algorithms that help improve work efficiency, and anyone can easily build an AI system by freely combining these algorithms.

     

    Easy automatic shift creation with AI cloud “HR BEST”

    HRBEST is a tool that automates complex shift creation with “combinatorial optimization” technology. Since shifts can be created according to the Labor Standards Law and industry rules, shift creation work for managers, who tend to be personalized, can be easily automated. Since it is a cloud service, it is always possible to respond to sudden shift changes and law revisions, and always keep the latest shift status.

     

    summary

    Machine learning engineers have a higher average annual income than general engineers, and it is expected that the level will continue to rise in the future. Many companies would like to acquire machine learning engineers to improve work efficiency and create businesses. However, it is difficult to hire machine learning engineers, and many companies may be worried that they will not be able to incorporate machine learning.  UMWELT / HRBEST is an AI tool that can be used without the need for an instrument learning engineer. Please take this article as an opportunity to contact TRYING.

     

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  • What are the differences between IT, ICT, and IoT

    What are the differences between IT, ICT, and IoT

    IT, ICT, IoT… all of these are important words that describe the technology fields that support  industry. Even if you have a rough understanding of what these terms mean, it can be difficult to explain the differences between them and how they relate to one another. In this article, we will introduce the meanings and differences between these words.

     

    What is IT?

    IT is an abbreviation for “Information Technology” and is a general term for technology that combines and utilizes communications such as the Internet with information devices such as computers.

    The Internet began to spread to the general public  after the release of Windows 95 in 1995. Between 1999 and 2000, ADSL and other broadband services for general individuals began to spread, mainly in urban areas.

    The term “IT revolution” first appeared around 2000. Yoshiro Mori, who was the Prime Minister at the time, mentioned the “e-Strategy” in his policy speech in the Diet, which led to the enactment of the IT Basic Law and related bills. However, during the policy speech, Mori also mispronounced “IT” as “it.” “IT revolution” won the New Words and Buzzwords Award in 2000.

    In 2006, the Policy” was launched, inheriting the ideas of the e-Initiative, with the aim of realizing a ubiquitous network society. FTTH using optical fiber also became common, ushering in an era of high-speed communications. In addition, the Ministry of Internal Affairs and Communications renamed its previous “IT Policy Principles” to the “ICT Policy Principles” in 2005. Around this time, the term ICT began to be used instead of IT.

     

    ICT is almost synonymous with IT

    ICT is an abbreviation for “Information and Communication Technology.” Overseas, ICT is more commonly used than IT.

    Like IT, ICT is a broad term that can refer to not only the internet and computers, but also a wide range of digital technologies, services, and businesses, including smartphones, big data, social media, and smart speakers.

    The difference between ICT and IT is that ICT tends to be used more to show how to utilize the Internet and computer-related technologies and to show future visions. Looking at how it is used in government agencies, the Ministry of Internal Affairs and Communications and the Ministry of Education, Culture, Sports, Science and Technology often use ICT, such as in “ICT Growth Strategy,” “ICT Regional Revitalization Award,” and “ICT Education,” while the Ministry of Economy, Trade and Industry often uses IT.

     

    What is IoT?

    IoT is an abbreviation for “Internet of Things.” It refers to a mechanism that enables things to be recognized, measured, and controlled remotely by connecting them to the Internet and exchanging information with each other.

    Traditionally, the main things that could connect to the Internet were computers and mobile phones. Later, smartphones, game consoles, music players, and televisions also began to connect to the Internet.

    As IoT becomes more commonplace in the future, the variety of connected things will explode in number, incomparable to today. Currently, IoT products that are beginning to spread include various electronic devices such as smart speakers, IoT home appliances such as lighting fixtures and air conditioners, and network cameras that can monitor pets while you are away. In addition
    , vehicles and transportation such as cars, buses, and trains, sensors and cameras installed in retail stores, medical equipment in hospitals, production equipment and robots installed on production lines in factories, inspection machines in warehouses, agricultural robots and self-driving agricultural machinery that are active in farmland, agricultural drones, wearable devices worn by visitors in theme parks, etc. will be connected to networks and play important roles in various fields.

     

    What is the difference between IoT and IoE?

    There are two terms related to IoT.
    The first is IoD (Internet of Digital). IoD refers to digital devices that are designed from the beginning to be connected to the Internet. Examples include computers, smartphones, and game consoles. Corporate mission-critical systems and servers are also types of IoD. The
    second is IoH (Internet of Human). IoH means that people, like things, are connected to the Internet. In other words, it is a system in which humans communicate with and operate things via computers and digital devices.

    And as a higher concept than IoT, IoD, and IoH, there is the term IoE (Internet of Everything), which means “the Internet of everything.”

    IoE is the final stage of IoT. It refers to services and businesses that are premised on connecting not only things, but also people, processes, data, places, and everything else to the Internet, as well as the technologies that make this possible.

    For example, let’s imagine a smart bed system in the medical field that can monitor the pulse rate, respiratory rate, and sleep/wake state of hospitalized patients. With IoT, it is possible to connect and manage the data obtained from this bed to a nurse call system or an electronic medical record database.

    However, in a world where IoE is widespread, the types of data sent from beds will increase and the data connected to them will also become more diverse. This will create an environment in which treatment optimized according to changes in the patient’s condition is automatically performed. If the data obtained there is accumulated, it is expected that treatment methods will eventually evolve to the next stage.

    IT, ICT, IoT, and IoE will continue to expand and impact every industry and field. In a few years, new services and business models that are completely different from those of today may be born. By understanding the differences between them and keeping a close eye on their trends, we may be able to see a vision of the future.

     

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  • What is SASE? Explaining the differences and relationship with Zero Trust

    What is SASE? Explaining the differences and relationship with Zero Trust

    The spread of telework has significantly changed the environment surrounding companies, and there is an increasing need to change security measures accordingly. In this context, one thing that is attracting attention is “SASE (SAS)”. In the future, the importance of SASE is expected to increase as the core of corporate security measures.
    In this article, we will explain the overview and mechanism of SASE, as well as its advantages and disadvantages, its necessity, and the difference between it and zero trust.

    What is SASE?

    SASE is an abbreviation for “Secure Access service Edge,” and is a term that represents a cloud service that provides network functions and security functions as an integrated whole, or the idea or concept behind it. In recent years, the spread of cloud services for business purposes and teleworking has made it difficult to provide sufficient measures with traditional security. In 2019, Gartner, Inc. of the United States proposed SASE, and it has attracted attention as a new way of network security.

    Differences and Relationships between SASE and Zero Trust

    “Zero Trust” is a concept similar to SASE. Zero Trust is a concept that “eliminates the concept of internal and external network boundaries, and protects against threats by verifying the safety of all access to information assets that need to be protected without trusting them.”

    Traditionally, internal networks were considered safe and external networks (such as the Internet) were considered dangerous, and security measures were implemented on the network boundary. However, in recent years, with the spread of cloud services and teleworking, the network boundary has become blurred, and traditional security measures are now considered insufficient.

    As a result, the idea of ​​zero trust has begun to attract attention, and SASE is being used as a concrete mechanism and service for achieving zero trust.

    The Need for SASE

    Security is not the only issue that arises with the expansion of cloud services and teleworking. As network and security environments become more complex, the operation and management of hardware and systems that need to be managed can become complicated, and there is also a need to efficiently process large amounts of traffic.

    By integrating network functions and security functions, SASE not only enhances security but also reduces the burden by making operation and management more efficient. It also enables efficient network design to prevent delays and deterioration of communication quality, which ultimately contributes to business efficiency.

    For these reasons, SASE is needed.

    How does SASE work?

    SASE is provided as a cloud service and can be accessed and used from a corporate network or a telework environment such as at home. It is a system that allows you to use uniform network security functions by accessing the internet, data centers, etc. through SASE from various networks.

    Security functions include SWG, CASB, FWaaS, ZTNA, etc., consolidating security measures that were previously implemented separately, enabling efficient network access.

    • SWG (Secure Web Gateway): Provides proxy functionality as a cloud service
    • CASB (Cloud Access Security Broker): Centralized management of cloud service utilization
    • FWaaS (FireWall as a Service): Providing firewall functions as a cloud service
    • ZTNA (Zero Trust Network Access): Access management based on zero trust

    Pros and Cons of SASE

    There are many benefits to using SASE. The most representative benefits are as follows:

    • Strengthening security measures
    • Reduce costs
    • Performance improvements
    • Policy Consolidation

    As explained above, security measures suited to today’s network environment can be implemented, and by centralizing operation and management as a cloud service, cost reductions and performance improvements can be expected. In addition, centralized management also makes it possible to integrate security policies.

    However, because it is used as the starting point for all access, if a failure occurs in the SASE-related network, it may affect the entire business. Of course, it is rare for a system to be designed in such a way that a single point of failure can affect the entire business, but it is still a disadvantage to keep in mind.

    SASE, which provides network and security functions as a cloud service, is a service and concept suited to the current environment, which is changing due to the spread of cloud services and teleworking. It is becoming difficult for companies to adequately respond to security measures with traditional perimeter security, and the need for zero trust thinking and SASE will increase.

    If you would like to learn more about Zero Trust, check out the following articles:

    Security measures based on the idea of ​​zero trust

    Furthermore, traditional password-only authentication methods will no longer be sufficient in the future, and measures to improve security will be essential. Hitachi Solutions Create offers authentication services to protect companies from information leaks and unauthorized access. Why not consider introducing them to use in-house systems and cloud services more safely?

     

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  • Security measures based on zero trust idea

    Security measures based on zero trust idea

    Some people may have heard of the term zero trust security but don’t know what it specifically means. In order to protect companies from risks such as cyber attacks and information leaks, it is important to understand zero trust security. In
    this article, we will explain the meaning of zero trust, why it is important, and how to incorporate zero trust security. Please refer to this article if you are involved in corporate security management.

     

    What is Zero Trust?

    Zero trust is a concept for improving information security. Zero trust means trusting nothing. The characteristic of zero trust is that it does not trust users or devices that attempt to access systems or databases, and always checks their safety.

    Why Zero Trust Security is Needed

    The reason for the need for zero trust security is the widespread use of cloud services and teleworking, which has led to an increase in the number of opportunities for risk to occur and a need for a more robust security model.

    In traditional security, a model called perimeter security was mainstream. Perimeter security is a security model that separates internal and external networks at a boundary to protect against external threats. However, perimeter security cannot deal with threats that have infiltrated inside the boundary.

    On the other hand, zero trust security has no concept of boundaries and verifies all targets. The reason zero trust security is attracting attention is that it can also handle threats such as malware that have infiltrated the internal network.

    The pros and cons of zero trust security

    Zero trust security has both advantages and disadvantages, so it is important to understand its characteristics when considering its implementation.

    Benefit 1: Improved security

    Implementing zero trust security can improve security. The advantage of zero trust security is that it can reduce the risk of unauthorized access, even if various cloud services are used in business. It can also deal with information leaks caused by internal fraud.

    Advantage 2: Accessible from anywhere

    Another benefit is that you can access it securely from anywhere, such as at home, in a co-working space, or in a satellite office. Zero trust security increases safety, especially for organizations that encourage remote work.

    Disadvantages: High implementation costs

    The disadvantage of zero trust security is the high implementation cost. Various efforts are required, such as reviewing the existing security system and selecting new solutions. In addition, education on the new security system and the preparation of manuals are also necessary. There are also costs involved in introducing and operating devices and systems to achieve zero trust security.

    Disadvantages: Work efficiency may decrease

    Another point to be aware of is the decrease in work efficiency. In a system that employs zero trust security, you must go through the login procedure every time. Depending on the content and method of work, the decrease in efficiency can be said to be a disadvantage of zero trust security.

    How to adopt zero trust security

    Zero Trust security can be adopted in the following ways:

    Identity Management

    Zero trust security requires a user ID to access a system or database. Unauthorized access is prevented by issuing a user ID and verifying it at the time of login.

    In addition, by introducing a multi-factor authentication system using users’ own devices, it is possible to prevent unauthorized use of user IDs.

    Managing Access Rights

    Even when using the same system, different users perform different tasks. Therefore, assigning different access permissions to each user is essential to achieving zero trust security.

    For example, it is necessary to manage the data by giving only viewing permissions to contractor IDs, while giving both viewing and editing permissions to employee IDs.

    Manage your activity history

    By managing the behavioral history of users who accessed the system, it is possible to detect and analyze security risks. A system that acquires access logs and monitors them in real time can achieve zero trust security.

    Zero trust security is a security model that does not trust any user or connection source and always verifies safety. It can also address risks such as malware infection and internal fraud that were difficult to prevent with the traditional border defense model.
    If you want to achieve strong cybersecurity, why not try zero trust security?

     

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  • What is CASB? Explaining the difference between CASB and SASE

    What is CASB? Explaining the difference between CASB and SASE

    In today’s business environment, the use of cloud services is expanding rapidly, and the associated information security issues are also increasing. CASB (Computer Access Security Platform) is attracting attention in this situation. CASB is a general term for security solutions that allow companies to safely use cloud services, but how does it differ from SASE (Sydney Access Security Platform), which is also an important concept in security?

    In this article, we will take a closer look at what CASB is, its key features, the benefits of adopting it, and how it differs from SASE.

     

    What is a CASB?

    CASB (Cloud Access Security Broker) is a solution that ensures security and maintains compliance when companies use cloud services. In recent years, as the use of cloud services for business purposes has increased, managing and protecting them has become a challenge. CASB is a tool to address this issue, and plays a role in visualizing and controlling the use of cloud services.

    Key features of a CASB

    A CASB has four main functions:

    ・Visualization and monitoring

    It provides visibility into all cloud services used by companies and monitors them in real time, making it possible to know which users are using which services and to detect abnormal activity early.

    Data protection

    It provides data classification and encryption, DLP (Data Loss Prevention) functions, and other features to prevent confidential information from leaking, and strengthens access control to ensure that only users with the appropriate permissions can access data.

    Compliance management

    Businesses must comply with various regulations, and CASBs provide the tools to meet compliance requirements in a cloud environment, helping businesses meet legal requirements and industry standards.

    Threat prevention

    It is equipped with security features such as malware detection and prevention, account hijacking prevention, and abnormal user behavior detection. It reduces security risks when using cloud services, and can also be used in combination with other features to deal with internal fraud.

    The difference between CASB and SASE

    When it comes to the topic of cloud security, SASE is frequently mentioned along with CASB. Understanding the difference between the two is important in taking appropriate security measures, so let’s take a look at the differences between them along with an overview of SASE.

    What is SASE?

    SASE (Secure Access Service Edge) is a new approach to cloud security, a solution that integrates network and security. While traditional network security relies on physical boundaries, SASE is cloud-based, enabling flexible and scalable security.

    For more information on SASE, please see this article:
    → ” What is SASE? Explaining the differences and relationship with Zero Trust “

    The difference between CASB and SASE

    SASE is not only a cloud security solution, but also a concept and way of thinking. While CASB is a tool for making cloud services safer, SASE integrates network and security.

    The differences between the two can be easily summarised in the following table:

    Role and ScopeTechnology IntegrationForm of delivery
    SASEAchieving Zero Trust and Network-wide SecurityA comprehensive solution that integrates technologies such as SD-WAN, CASB, FW, and ZTNA.Cloud Native
    CASBSafe cloud usage, security for using cloud servicesSpecializing in making cloud services safeCloud service or on-premise

    SASE and CASB may seem similar at first glance, but in reality, CASB is used as one of the functions and means to realize SASE.

    Benefits of Introducing CASB

    The benefits of implementing a CASB include:

    • Strengthening security measures
    • Flexible Access Management
    • Maintaining Compliance
    • Optimizing Cloud Usage
    • Threat detection and response

    CASB monitors the use of cloud services and prevents information leaks by providing data encryption and data loss prevention (DLP) functions. It also has the ability to detect abnormal activities in real time, allowing for rapid response. In addition, different access permissions can be set for each user, allowing access only to necessary data and services, enhancing security. These security measures are effective against the recent increase in the use of cloud services for business purposes and remote work.

    In addition, CASBs provide the tools and capabilities to help companies comply with various regulations such as GDPR and HIPAA, and they also provide visibility into cloud service usage, helping to reduce unnecessary costs and streamline operations.

    In addition, the AI ​​function can detect attacks that could not be detected by conventional security solutions, significantly strengthening a company’s security system.

    Incorporate a CASB into your security strategy

    CASB is an essential security solution in today’s world where the use of cloud services is increasing. By implementing CASB, companies can effectively use cloud services while reducing security risks and maintaining compliance. By incorporating CASB into your security strategy, your company’s IT infrastructure will become safer and more efficient.

     

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  • Benefits of IoT and use cases by field

    Benefits of IoT and use cases by field

    What benefits will IoT bring to us, in what fields is it used, and how will it develop in the future? In this article, we will introduce examples of IoT use in different fields.

     

    What is IoT?

    IoT is a mechanism that enables things to be recognized, measured, and controlled remotely by connecting them to the Internet and exchanging information. It is an acronym of “Internet of Things” and is often translated as “Internet of Things” in Japanese.

    Benefits of IoT

    What kind of convenience and usefulness will the widespread use of IoT bring? Let’s take a look at the benefits for users and companies.

    1. Improved user convenience

    IoT home appliances and smart houses that are already in practical use are accepted by users as convenient products. Representative examples include network cameras and door lock systems that can be remotely controlled from a smartphone while away from home, and air conditioners that automatically adjust to the optimum temperature according to the resident’s preferences, lifestyle rhythm, season, and changes in the outside air temperature.

    As IoT becomes more widespread in society, it is thought that the manufacturing industry will become more like a service industry. For example, if a product has a defect, that information will be sent to the manufacturer, so that appropriate measures can be taken immediately.

    For users, it is like receiving real-time, almost automated after-sales service or support. It is also possible to imagine a system in which parts are automatically delivered and replenished before consumable parts stop functioning. It will also be possible to realize services that allow users to ask questions about how to use the product through the product and receive advice and suggestions.

    2. Corporate efficiency and cost reduction

    IoT will enable companies that provide products to accurately grasp consumer needs and optimize supply and demand. Manufacturers in particular will be able to manufacture products that are definitely in demand, rather than just making products based on predictions of what will sell.

    Factories that utilize IoT are also becoming more common. By connecting production equipment equipped with sensors to a network, the operating status can be visualized, and an optimized production system can be maintained by analyzing data obtained from production equipment and machines and linking it to a production management system. It is said that factories can achieve thorough efficiency and cost reduction by adopting IoT.

    3. Creating business opportunities for companies

    By obtaining huge amounts of data through IoT, companies will be able to grasp diverse consumer demands. Utilizing that big data will also create new business opportunities. IoT has already begun to be used in many industries, including the service industry, logistics, medical care, and agriculture, and it is expected that it will give rise to completely new businesses in the future.

    Types of IoT and their use cases

    There are three types of IoT: IoT that operates things, IoT that knows the state of things, IoT that detects the movement of things, and IoT that communicates between things. Below, we will introduce examples of each. There are also examples of use cases where different IoTs are combined together.

    1. IoT examples for controlling objects

    IoT allows you to operate cameras, door locks, home appliances, healthcare devices, etc. using a smartphone. You can turn the power on and off, adjust the intensity, and perform other operations. For example, a product that allows you to monitor your pets while you are away using a network camera, talk to them through a speaker, and feed them became a hot topic.

    2. IoT examples for knowing the status of things

    IoT is a technology that monitors the condition of things and keeps track of them in real time. A typical example would be the wearable devices used in medical settings. Products that issue warning alerts when a patient’s health condition deteriorates, and contact lenses that can manage blood sugar levels have also been developed. In addition to wearable devices, products called “smart beds” that can monitor pulse rate, breathing rate, and sleep/wake states have also appeared.

    Additionally, in the agricultural sector, experiments have begun on “smart agriculture,” which uses IoT to monitor the environment inside greenhouses where vegetables and other crops are grown, and remotely controls temperature, air conditioning balance, and watering and fertilizer supply.

    3. IoT examples for detecting the movement of objects

    This is a type of IoT that detects the movement of objects or people carrying those objects and takes action. For example, a demonstration experiment is being conducted in which multiple IoT sensors are installed in key locations within a shopping facility, and customers’ smartphones and an app that allows them to use coupons are used to analyze their visit status by combining their movements and attributes.

    As IoT that detects motion becomes more widespread, systems that send information about sales and other special offers to the smartphones of regular or potential customers when they approach a shopping facility will likely become common.

    4. IoT examples of communication between things

    There are two types of IoT, which allows things to communicate with each other: IoT where machines collect information from other machines, and IoT where machines control other machines.

    A typical example of IoT where machines collect information from other machines is the Vehicle Information and Communications System (VICS). Currently, sensors installed on highways measure road information such as congestion and traffic regulations, and the VICS center processes the information and transmits it in real time to car navigation systems from radio beacons installed on the highway. In the future, it is expected that VICS will be able to cover even more detailed and extensive road information by having cars running on the roads themselves become IoT sensors and collect and analyze large amounts of information.

    An example of IoT where machines control other machines is an automatic lighting control system for buildings. Motion sensors installed in the building detect the presence of people, and the control device adjusts the brightness of the lights based on that information. Other systems that control air conditioning are also in the practical stage.

    IoT has been introduced into various fields and is already producing many benefits. It is expected to become even more widespread in the near future and dramatically change our living environment. Please keep an eye on its trends.

     

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  • What is Industry 4.0? Explaining the difference with IoT

    What is Industry 4.0? Explaining the difference with IoT

    “Industry 4.0” is closely related to IoT and is said to be an important term that will influence the future direction of manufacturing in Japan. We will answer questions such as what is Industry 4.0, what kind of future does it paint, and how it is related to and different from IoT.

     

    What is Industry 4.0?

    Industry 4.0 (the fourth industrial revolution) is a national project  which has established a domestic industry-government-academia collaboration system, and has also attracted attention in Japan with the advancement of IoT. At the heart of
    this concept is the idea of ​​the “smart factory” (thinking factory).

     

    What is a smart factory in Industry 4.0?

    A smart factory is a system in which all machinery and equipment within a factory are connected to the Internet, streamlining the manufacturing process and enabling the efficient large-scale production of small quantities of a wide variety of high-added-value products.

    It is said that to make factories smarter, it is essential to network the engineering and supply chains using not only the Internet, but also IoT, big data, AI, industrial robots, etc. The essence of a smart factory is a factory that makes maximum use of advanced technologies such as IoT and robots and is connected by a network.

     

    What is the goal of Industry 4.0?

    What exactly does Industry 4.0 intend to achieve? The following three points are considered to be particularly important:

    1. Realization of dynamic cell production

    “Dynamic cell production” was devised as a way to realize large-scale production of a wide variety of low-volume, high-value-added products using smart factories. Dynamic cell production is said to be an evolved production method that combines the advantages of traditional “line production” and “cell production,” in which products are assembled by one person or a small team of workers.

    In dynamic cell production, the line processes are classified into several types, and the robots responsible for assembly at each process exchange information in real time via a network with the cloud, higher-level systems, surrounding equipment, and on-site workers, and proceed with the optimized number and variety of production according to the situation.

    2. Appealing to mass customization

    By further advancing dynamic cell production, it will eventually be possible to produce products with individually different specifications. The manufacturing technique of producing products that reflect diverse customer needs in a timely manner, starting from “lot size 1,” and providing them to the market without increasing costs is called “mass customization.” This term is a combination of mass production, which means mass production, and customization, which means made-to-order production.

    It is predicted that in the future, Industry 4.0 will see many smart factories being connected to each other, so that a country’s entire manufacturing industry will function as if it were one large smart factory.

    Mass customization will be realized in the most ideal way in such a future environment. Each product with specifications changed according to needs will be produced quickly and smoothly by automatically selecting the most efficient line and process in the supply chain. It has been announced that this will enable everyone to obtain custom-made products quickly and at low prices.

    3. Evolving manufacturing with cyber-physical systems (CPS)

    Industry 4.0 aims to evolve manufacturing through “cyber-physical systems” that collect diverse data from the real world, or physical world, using sensor networks and other means, and process and analyze it using computer systems in cyberspace.

    A sensor network is a network of interconnected sensors that measure data, while a cyber-physical system is a system or service that creates an efficient and advanced society by closely linking computing power in the real world and cyberspace.

    For example, when a product manufactured through mass customization is delivered to a consumer, the product itself then acts as a data collection terminal, sending data on usage and consumer needs to the design and manufacturing site, creating a cycle.

    Once such a cyber-physical system infrastructure is in place, it is expected that intelligent production systems will be built in which all data related to manufacturing, from design and development to production, will be accumulated and analyzed, and will operate autonomously to deliver products to consumers.

     

    What is the difference between IoT and Industry 4.0?

    IoT is translated as “Internet of Things”. IoT is a mechanism in which various things are connected to the Internet and take necessary actions by exchanging information. In IoT, things are basically connected to the Internet to exchange information.

    On the other hand, in Industry 4.0, not only are things connected to the Internet, but things are also connected to each other. Furthermore, collections of things, or business processes, are also connected to each other and exchange information. These complex connections allow for autonomous and automatic operation while maintaining an optimized production system, which is the new form of manufacturing in Industry 4.0.

     

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  • What is a security incident? Explaining the types and countermeasures for companies

    What is a security incident? Explaining the types and countermeasures for companies

    In recent years, with the advancement of information technology, companies need to be careful about security incidents. Security incidents occur due to various factors such as cyber attacks, natural disasters, human error, and physical theft, and can have a significant impact on the survival of a company. Responding to security incidents has become essential for continuing corporate activities.

    In this article, we will explain the basics of security incidents, including their overview, types, and the measures that companies should take against them.

     

    What is a security incident?

    A security incident is an event that materializes a threat to the confidentiality, integrity, or availability of an information system. Simply put, it can be called a “security threat.”

    Specifically, these include data leaks due to cyber attacks, system downtime, damage to data centers due to natural disasters, information leaks due to human error, and physical theft. The occurrence of security incidents can have a significant impact on a company’s operations and, in some cases, may even develop into legal issues. For this reason, in today’s information-driven society, responding to security incidents is essential regardless of industry or business type.

    Main types of security incidents

    Security incidents are classified into several types depending on the cause of their occurrence. Here we will provide an overview of each type.

    Security incidents resulting from cyber attacks

    Security incidents caused by cyber attacks are the most common and serious threat to companies. Major examples of cyber attacks include malware infection, ransomware attacks, and DoS attacks.

    Malware infection:

    A general term for malicious software such as computer viruses, spyware, and Trojan horses that invade systems and steal or destroy data. In recent years, there has been an increase in targeted attacks targeting important corporate data.

    Ransomware attacks:

    These attacks encrypt systems and demand a ransom to unlock them, often threatening to make data public or lose it forever if payment is not made, severely impacting the operations of companies.

    Denial of Service attacks:

    Also known as a denial of service attack, this is an attack that sends a large amount of traffic to a specific network or system, causing normal service to be halted. A DoS attack causes a website or online service to become temporarily unavailable.

    Security incidents due to natural disasters

    Cyberattacks are not the only cause of security incidents. They can also be caused by natural disasters such as earthquakes, floods, and typhoons. Natural disasters can cause physical damage to data centers and server facilities, resulting in system downtime, data loss, and business interruptions. Japan is a country that is prone to natural disasters, including earthquakes. Natural disasters are difficult to predict, and the damage they cause can be severe, so advance measures are important.

    Security incidents caused by human error

    Human error also contributes to security incidents, such as sending emails to the wrong person, accidentally deleting data, accidentally disclosing confidential information, etc. These errors can be prevented to some extent by educating employees and improving work processes.

    In addition, there may be cases where employees cause security incidents with malicious intent. It is also important to be careful of man-made security incidents, such as employees obtaining unfair money through internal fraud or using confidential information to change jobs.

    Other security incidents

    Security incidents also include physical theft or vandalism, such as theft of computers or mobile devices from an office or unauthorized entry into a facility, which can be prevented through improved security measures and access management.

    Security incident countermeasures that companies should take

    Dealing with security incidents requires both technical and organizational/operational measures.

    Technical countermeasures

    Technical measures refer to specific means to protect systems and data. For example, “strengthening network security” by introducing firewalls and intrusion detection/prevention systems (IDS/IPS) to prevent unauthorized access from outside is one example. In addition, it is also important to provide secure remote access using VPNs.

    Other effective measures include data encryption and access management to prevent easy access to confidential information and to make it difficult to decipher even if it is leaked.

    Organizational and operational measures

    In addition to technical measures, it is also important to have unified security operation measures across the entire organization. First of all, regularly provide education and training to raise employees’ security awareness. This will help prevent human error and internal fraud while learning new security knowledge.

    It is also important to consider how to respond after a security incident occurs. Decide in advance how your organization will respond to an incident, such as by formulating an incident response plan and an emergency communication plan, and share this information within the company.

    Security incidents are an unavoidable threat to companies, but the risk can be minimized by taking appropriate measures. It is important to combine technical measures with organizational and operational measures to raise security awareness throughout the company. Considering the possibility that new threats will continue to emerge in the future, we should always collect the latest information and consider how to respond to security incidents.

     

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  • What is a security incident? Explaining the types and countermeasures for companies

    What is a security incident? Explaining the types and countermeasures for companies

    In recent years, with the advancement of information technology, companies need to be careful about security incidents. Security incidents occur due to various factors such as cyber attacks, natural disasters, human error, and physical theft, and can have a significant impact on the survival of a company. Responding to security incidents has become essential for continuing corporate activities.

    In this article, we will explain the basics of security incidents, including their overview, types, and the measures that companies should take against them.

     

    What is a security incident?

    A security incident is an event that materializes a threat to the confidentiality, integrity, or availability of an information system. Simply put, it can be called a “security threat.”

    Specifically, these include data leaks due to cyber attacks, system downtime, damage to data centers due to natural disasters, information leaks due to human error, and physical theft. The occurrence of security incidents can have a significant impact on a company’s operations and, in some cases, may even develop into legal issues. For this reason, in today’s information-driven society, responding to security incidents is essential regardless of industry or business type.

    Main types of security incidents

    Security incidents are classified into several types depending on the cause of their occurrence. Here we will provide an overview of each type.

    Security incidents resulting from cyber attacks

    Security incidents caused by cyber attacks are the most common and serious threat to companies. Major examples of cyber attacks include malware infection, ransomware attacks, and DoS attacks.

    Malware infection:

    A general term for malicious software such as computer viruses, spyware, and Trojan horses that invade systems and steal or destroy data. In recent years, there has been an increase in targeted attacks targeting important corporate data.

    Ransomware attacks:

    These attacks encrypt systems and demand a ransom to unlock them, often threatening to make data public or lose it forever if payment is not made, severely impacting the operations of companies.

    Denial of Service attacks:

    Also known as a denial of service attack, this is an attack that sends a large amount of traffic to a specific network or system, causing normal service to be halted. A DoS attack causes a website or online service to become temporarily unavailable.

    Security incidents due to natural disasters

    Cyberattacks are not the only cause of security incidents. They can also be caused by natural disasters such as earthquakes, floods, and typhoons. Natural disasters can cause physical damage to data centers and server facilities, resulting in system downtime, data loss, and business interruptions. Japan is a country that is prone to natural disasters, including earthquakes. Natural disasters are difficult to predict, and the damage they cause can be severe, so advance measures are important.

    Security incidents caused by human error

    Human error also contributes to security incidents, such as sending emails to the wrong person, accidentally deleting data, accidentally disclosing confidential information, etc. These errors can be prevented to some extent by educating employees and improving work processes.

    In addition, there may be cases where employees cause security incidents with malicious intent. It is also important to be careful of man-made security incidents, such as employees obtaining unfair money through internal fraud or using confidential information to change jobs.

    Other security incidents

    Security incidents also include physical theft or vandalism, such as theft of computers or mobile devices from an office or unauthorized entry into a facility, which can be prevented through improved security measures and access management.

    Security incident countermeasures that companies should take

    Dealing with security incidents requires both technical and organizational/operational measures.

    Technical countermeasures

    Technical measures refer to specific means to protect systems and data. For example, “strengthening network security” by introducing firewalls and intrusion detection/prevention systems (IDS/IPS) to prevent unauthorized access from outside is one example. In addition, it is also important to provide secure remote access using VPNs.

    Other effective measures include data encryption and access management to prevent easy access to confidential information and to make it difficult to decipher even if it is leaked.

    Organizational and operational measures

    In addition to technical measures, it is also important to have unified security operation measures across the entire organization. First of all, regularly provide education and training to raise employees’ security awareness. This will help prevent human error and internal fraud while learning new security knowledge.

    It is also important to consider how to respond after a security incident occurs. Decide in advance how your organization will respond to an incident, such as by formulating an incident response plan and an emergency communication plan, and share this information within the company.

    Security incidents are an unavoidable threat to companies, but the risk can be minimized by taking appropriate measures. It is important to combine technical measures with organizational and operational measures to raise security awareness throughout the company. Considering the possibility that new threats will continue to emerge in the future, we should always collect the latest information and consider how to respond to security incidents.

     

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