Mining map Mini exercise
Publish: 2021-05-01 23:51:07
1. Polar bears can breed because they need two polar bears. Polar bears breed with ham
2.
Although I don't know the specific miner maps, I think you can go to the Mini World Mini collection to find them, maybe there will be
3. Take tools, weapons, torches and pay attention to the magma. There is magma nearby. You can hear the sound
4.
I'm not sure. Every map has a lot of mines
5. The author's Mini number is 594042979. I've played this map of omnipotent clods. It's very interesting!
6. The eastern kingdom of Kalimdor
7. Preface:
in the last article (in-depth collation of the core points of the EU General Data Protection Act (gdpr), I shared the core points of the gdpr bill for you, so that enterprises can intuitively understand what gdpr is and what impact it will have on their future business. This paper will focus on the core points of gdpr to deeply analyze how enterprises in the Internet of things instry should respond. The response plan here involves system architecture, personnel management, process management, risk assessment, business logic, emergency response and many other links. Due to the different business situations of different enterprises, the following content can be used as an analysis method of self inspection of Internet of things enterprises
the particularity of the Internet of things instry is that many devices are not connected to the Internet, so there is no risk of user privacy leakage. Mobile phone networking represent the general trend name. Sex control and data processing will directly or indirectly involve a large number of personal data, such as name, gender, age, ID number, cell phone number, etc., and on the other hand, more data about user behavior will be collected because of the need to operate and monitor the device and user data. Therefore, the impact of gdpr on Internet of things enterprises is very far-reaching and important
as a security solution company of Internet of things, Qinglian cloud has accumulated experience in network security, cloud security, hacker attack and defense confrontation, data privacy protection and other fields for many years, and summarized the following key points according to the response ideas of domestic Internet of things enterprises after the implementation of gdpr, It can be used as a reference direction for enterprises in the process of practicing gdpr compliance, so as to share and discuss with you<
suggestions for domestic Internet of things enterprises to deal with gdpr:
1. Direct attention of enterprise executives
2. Reasonable distinction between data controllers and data processors
3. Protection of privacy from the beginning of design
4. Clear data authorization consent from customers
5. Identification of data storage location
6. Identification of data types and risks
7 Use authorization of identification data
8, migration and transmission ability of identification data
9, ability to clear personal data when necessary
10, ability to quickly identify and timely report data leakage events
11, principle of data minimization
12, anonymization of data
13, confidentiality of network communication and data integrity
14 Ensure strong identity authentication of network communication
15, attach importance to data lifecycle management
16, attach importance to internal privacy control
17, check whether the third-party suppliers meet gdpr
18, consider setting up special privacy protection personnel
19, have other security compliance requirements
20 Keep close cooperation with professional safety companies
the direct attention of enterprise executives
whether it is gdpr or other regulatory requirements of safety compliance, it is more closely related to the enterprise management / R & D process. The promotion of internal process depends more on the attention and practical determination of executives. To promote the correct implementation of a process needs to be carried out from top to bottom in an orderly manner. If the senior executives do not have enough awareness or attach enough importance to promoting the compliance process, it will often cause a lot of waste of human time cost and affect the progress of normal business. So we put the top priority on the top of the list<
distinguish data controller and data processor reasonably
there is a clear description of controller and processor in gdpr. In the practice of gdpr, it is very important for enterprises to make clear whether they belong to the controller or processor of data. For example: if an enterprise uses Google Analytics (or other third-party data analysis service provider) to analyze the user behavior of a website, then the enterprise is the data controller and Google Analytics is the data processor. When the data subject (consumer) implements the "forgotten right" according to the requirements of gdpr, the enterprise has the responsibility to fulfill the legitimate requirements of users, and the enterprise should be able to delete the user's personal data handed over to the third-party data analysis service provider
protect privacy from the beginning of design. The reason is very simple. Security is the cornerstone of IT system. If there are security loopholes in the basic IT system, especially for the Internet of things instry, the security problem of business logic can not be solved by batch remote upgrade. Internet of things enterprises should bring security factors into the scope of architecture design at the beginning of designing system architecture. Only by early intervention of safety can we avoid more serious enterprise losses caused by safety accidents in the later period<
clearly obtain the data authorization consent of the customer
gdpr also has a clear description here, which requires the enterprise to tell the customer in a very obvious and straightforward way what data will be collected (similar to the permission authorization of APP), especially for the Internet of things procts for minors (such as children's watches, children's story machines, etc.), The data can only be collected with the direct authorization of the guardian
identify where data is stored
data is part of an enterprise's IT assets. Before practicing gdpr, one of the things enterprises must do is to identify where the data exists. The underlying architecture of the Internet of things is cloud computing. Cloud computing will use different data storage technologies to store different types of data, such as redis to store cache data, Hadoop to store offline large log files, and Cassandra to store some fragmented small files. The technical director of an enterprise must be clearly aware of which data storage technologies or components are used internally, and which types of data are stored in different components. Identifying the "data battlefield" is the first step of data privacy protection
identify the type and risk of data
after identifying the location of data storage, risk assessment of data assets is needed. Think about the types of data stored by enterprises: such as personal identity data, positioning data, behavior data, financial data? What are the types of data: integer? Floating point? Boolean? Picture / video? What are the risks of different data leakage: for example, will the user's credit card be stolen? Will users suffer from spam attacks? Will user identity be counterfeited? Will it cause users to be tracked? And so on, according to the data risk model established by the enterprise, it can provide strong support for the targeted deployment of security solutions in the future
identify the authorization of data usage
in most data usage scenarios, enterprises are not the only ones who have complete control and processing rights over data. In big data solutions, it is often necessary to use the ability of external third-party enterprises to conct in-depth data mining and analysis. At this time, the authorization management of data use is extremely important. Enterprises need to know clearly which data exist and exchange with the third party's data service or directly send the data to the third party. When this happens, the enterprise becomes the controller of the data. If the third-party service provider has the problem of data leakage, according to the regulations of gdpr, the enterprise as the controller also has joint and several liability<
identify the ability of data migration and transmission
in gdpr, the data subject (consumer) has the right to transmit personal information to other indivials or organizations. This requires that when designing the system architecture, enterprises should be able to support data format processing, and be portable, and share data among multiple suppliers. At the same time, they also need to have a solution for data security transmission, so as to ensure data encryption, integrity and strict two-way identity authentication in the process of transmission
the right to be forgotten, which can clear personal data when necessary, is also highlighted in gdpr. The enterprise must be able to delete some data specified by users or no longer allowed by users. Enterprises should be able to quickly locate the data, delete the user data, and notify the third-party data service provider of the data to be deleted (if the data is used by the third party)
the ability to quickly identify and timely report data leakage events
I think this ability is very important and very difficult. There are two difficulties: 1. How can enterprises quickly identify their own data leakage? Throughout the history or recent cases of data leakage, enterprises are basically behind the scenes; 2. Does the enterprise have the ability (COURAGE) to timely report data leakage events to the regulators and data subjects within 72 hours specified in gdpr? Why is this ability difficult? I believe that enterprise managers can feel it. In fact, it is not entirely a technical ability
follow the principle of data minimization
there is an important principle in the design of security architecture: minimizing permissions. That is to say, risk assessment is carried out for the business, and only the minimum permissions that can meet the business operation are provided, such as opening as few ports as possible, disabling root permissions, etc. Gdpr clearly stipulates the principle of data minimization, that is, collecting user data as little as possible to meet business needs. Generally speaking, with less functions, there will be less risks, which is the same in data security<
anonymization of data
there is a clear official definition of "anonymization" in gdpr. There are two meanings: 1. Take the system architecture of Qinglian cloud as an example, carry out sub database / classified encryption storage for different types of data of users and devices, so as to avoid disclosing all and complete personal data of users at one time in case of data leakage; 2, anonymous data processing is done for sensitive data, such as hiding the middle date data section when recording the ID number, avoiding direct positioning or pointing to a certain natural person because of data leakage.
to ensure the confidentiality and data integrity of network communication
there are two key points: confidentiality and integrity. Qinglian cloud's system architecture has built-in self-developed Internet of things security access gateway system. The gateway can not only provide a variety of data encryption methods (AES / DES / SSL, etc.), but also carry out security signature and legitimacy verification for each data packet, so as to ensure that the data can resist the device replay attacks initiated by hackers in the process of encrypted transmission, Achieve safe and stable data transmission of Internet of things
ensure strong identity authentication of network communication
identity authentication must be bidirectional rather than unidirectional. For the Internet of things instry, identity authentication mainly includes equipment and cloud, equipment and device end, client and cloud, client and device end, cloud and third-party interface and cloud itself. In the system architecture of Qinglian cloud, this series of identity authentication mechanisms are also implemented by the Internet of things security access gateway system, which can resist the device forgery and other data forgery attacks initiated by hackers
pay attention to data lifecycle management
for the enterprise's R & D process, Microsoft proposed SDL (security development lifecycle), which is divided into seven parts, from training to final emergency response. The same is true for data, and enterprises should
in the last article (in-depth collation of the core points of the EU General Data Protection Act (gdpr), I shared the core points of the gdpr bill for you, so that enterprises can intuitively understand what gdpr is and what impact it will have on their future business. This paper will focus on the core points of gdpr to deeply analyze how enterprises in the Internet of things instry should respond. The response plan here involves system architecture, personnel management, process management, risk assessment, business logic, emergency response and many other links. Due to the different business situations of different enterprises, the following content can be used as an analysis method of self inspection of Internet of things enterprises
the particularity of the Internet of things instry is that many devices are not connected to the Internet, so there is no risk of user privacy leakage. Mobile phone networking represent the general trend name. Sex control and data processing will directly or indirectly involve a large number of personal data, such as name, gender, age, ID number, cell phone number, etc., and on the other hand, more data about user behavior will be collected because of the need to operate and monitor the device and user data. Therefore, the impact of gdpr on Internet of things enterprises is very far-reaching and important
as a security solution company of Internet of things, Qinglian cloud has accumulated experience in network security, cloud security, hacker attack and defense confrontation, data privacy protection and other fields for many years, and summarized the following key points according to the response ideas of domestic Internet of things enterprises after the implementation of gdpr, It can be used as a reference direction for enterprises in the process of practicing gdpr compliance, so as to share and discuss with you<
suggestions for domestic Internet of things enterprises to deal with gdpr:
1. Direct attention of enterprise executives
2. Reasonable distinction between data controllers and data processors
3. Protection of privacy from the beginning of design
4. Clear data authorization consent from customers
5. Identification of data storage location
6. Identification of data types and risks
7 Use authorization of identification data
8, migration and transmission ability of identification data
9, ability to clear personal data when necessary
10, ability to quickly identify and timely report data leakage events
11, principle of data minimization
12, anonymization of data
13, confidentiality of network communication and data integrity
14 Ensure strong identity authentication of network communication
15, attach importance to data lifecycle management
16, attach importance to internal privacy control
17, check whether the third-party suppliers meet gdpr
18, consider setting up special privacy protection personnel
19, have other security compliance requirements
20 Keep close cooperation with professional safety companies
the direct attention of enterprise executives
whether it is gdpr or other regulatory requirements of safety compliance, it is more closely related to the enterprise management / R & D process. The promotion of internal process depends more on the attention and practical determination of executives. To promote the correct implementation of a process needs to be carried out from top to bottom in an orderly manner. If the senior executives do not have enough awareness or attach enough importance to promoting the compliance process, it will often cause a lot of waste of human time cost and affect the progress of normal business. So we put the top priority on the top of the list<
distinguish data controller and data processor reasonably
there is a clear description of controller and processor in gdpr. In the practice of gdpr, it is very important for enterprises to make clear whether they belong to the controller or processor of data. For example: if an enterprise uses Google Analytics (or other third-party data analysis service provider) to analyze the user behavior of a website, then the enterprise is the data controller and Google Analytics is the data processor. When the data subject (consumer) implements the "forgotten right" according to the requirements of gdpr, the enterprise has the responsibility to fulfill the legitimate requirements of users, and the enterprise should be able to delete the user's personal data handed over to the third-party data analysis service provider
protect privacy from the beginning of design. The reason is very simple. Security is the cornerstone of IT system. If there are security loopholes in the basic IT system, especially for the Internet of things instry, the security problem of business logic can not be solved by batch remote upgrade. Internet of things enterprises should bring security factors into the scope of architecture design at the beginning of designing system architecture. Only by early intervention of safety can we avoid more serious enterprise losses caused by safety accidents in the later period<
clearly obtain the data authorization consent of the customer
gdpr also has a clear description here, which requires the enterprise to tell the customer in a very obvious and straightforward way what data will be collected (similar to the permission authorization of APP), especially for the Internet of things procts for minors (such as children's watches, children's story machines, etc.), The data can only be collected with the direct authorization of the guardian
identify where data is stored
data is part of an enterprise's IT assets. Before practicing gdpr, one of the things enterprises must do is to identify where the data exists. The underlying architecture of the Internet of things is cloud computing. Cloud computing will use different data storage technologies to store different types of data, such as redis to store cache data, Hadoop to store offline large log files, and Cassandra to store some fragmented small files. The technical director of an enterprise must be clearly aware of which data storage technologies or components are used internally, and which types of data are stored in different components. Identifying the "data battlefield" is the first step of data privacy protection
identify the type and risk of data
after identifying the location of data storage, risk assessment of data assets is needed. Think about the types of data stored by enterprises: such as personal identity data, positioning data, behavior data, financial data? What are the types of data: integer? Floating point? Boolean? Picture / video? What are the risks of different data leakage: for example, will the user's credit card be stolen? Will users suffer from spam attacks? Will user identity be counterfeited? Will it cause users to be tracked? And so on, according to the data risk model established by the enterprise, it can provide strong support for the targeted deployment of security solutions in the future
identify the authorization of data usage
in most data usage scenarios, enterprises are not the only ones who have complete control and processing rights over data. In big data solutions, it is often necessary to use the ability of external third-party enterprises to conct in-depth data mining and analysis. At this time, the authorization management of data use is extremely important. Enterprises need to know clearly which data exist and exchange with the third party's data service or directly send the data to the third party. When this happens, the enterprise becomes the controller of the data. If the third-party service provider has the problem of data leakage, according to the regulations of gdpr, the enterprise as the controller also has joint and several liability<
identify the ability of data migration and transmission
in gdpr, the data subject (consumer) has the right to transmit personal information to other indivials or organizations. This requires that when designing the system architecture, enterprises should be able to support data format processing, and be portable, and share data among multiple suppliers. At the same time, they also need to have a solution for data security transmission, so as to ensure data encryption, integrity and strict two-way identity authentication in the process of transmission
the right to be forgotten, which can clear personal data when necessary, is also highlighted in gdpr. The enterprise must be able to delete some data specified by users or no longer allowed by users. Enterprises should be able to quickly locate the data, delete the user data, and notify the third-party data service provider of the data to be deleted (if the data is used by the third party)
the ability to quickly identify and timely report data leakage events
I think this ability is very important and very difficult. There are two difficulties: 1. How can enterprises quickly identify their own data leakage? Throughout the history or recent cases of data leakage, enterprises are basically behind the scenes; 2. Does the enterprise have the ability (COURAGE) to timely report data leakage events to the regulators and data subjects within 72 hours specified in gdpr? Why is this ability difficult? I believe that enterprise managers can feel it. In fact, it is not entirely a technical ability
follow the principle of data minimization
there is an important principle in the design of security architecture: minimizing permissions. That is to say, risk assessment is carried out for the business, and only the minimum permissions that can meet the business operation are provided, such as opening as few ports as possible, disabling root permissions, etc. Gdpr clearly stipulates the principle of data minimization, that is, collecting user data as little as possible to meet business needs. Generally speaking, with less functions, there will be less risks, which is the same in data security<
anonymization of data
there is a clear official definition of "anonymization" in gdpr. There are two meanings: 1. Take the system architecture of Qinglian cloud as an example, carry out sub database / classified encryption storage for different types of data of users and devices, so as to avoid disclosing all and complete personal data of users at one time in case of data leakage; 2, anonymous data processing is done for sensitive data, such as hiding the middle date data section when recording the ID number, avoiding direct positioning or pointing to a certain natural person because of data leakage.
to ensure the confidentiality and data integrity of network communication
there are two key points: confidentiality and integrity. Qinglian cloud's system architecture has built-in self-developed Internet of things security access gateway system. The gateway can not only provide a variety of data encryption methods (AES / DES / SSL, etc.), but also carry out security signature and legitimacy verification for each data packet, so as to ensure that the data can resist the device replay attacks initiated by hackers in the process of encrypted transmission, Achieve safe and stable data transmission of Internet of things
ensure strong identity authentication of network communication
identity authentication must be bidirectional rather than unidirectional. For the Internet of things instry, identity authentication mainly includes equipment and cloud, equipment and device end, client and cloud, client and device end, cloud and third-party interface and cloud itself. In the system architecture of Qinglian cloud, this series of identity authentication mechanisms are also implemented by the Internet of things security access gateway system, which can resist the device forgery and other data forgery attacks initiated by hackers
pay attention to data lifecycle management
for the enterprise's R & D process, Microsoft proposed SDL (security development lifecycle), which is divided into seven parts, from training to final emergency response. The same is true for data, and enterprises should
8. Black machine is a machine through illegal means! After all, the American version of the machine on sale in the United States! From the United States into the inland machine, there are smuggling and theft! I don't know if you belong to that! Foreign laws are perfect! If you lose your mobile phone, you will report it through IMEI! And on record!
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