CN110753025A - Big data security access control method - Google Patents
Big data security access control method Download PDFInfo
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- CN110753025A CN110753025A CN201910025394.9A CN201910025394A CN110753025A CN 110753025 A CN110753025 A CN 110753025A CN 201910025394 A CN201910025394 A CN 201910025394A CN 110753025 A CN110753025 A CN 110753025A
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000004458 analytical method Methods 0.000 claims abstract description 44
- 239000000725 suspension Substances 0.000 claims description 48
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 claims description 14
- 229910052710 silicon Inorganic materials 0.000 claims description 14
- 239000010703 silicon Substances 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000009826 distribution Methods 0.000 claims description 6
- 230000003828 downregulation Effects 0.000 claims description 6
- 230000003068 static effect Effects 0.000 claims description 6
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 4
- 229910052744 lithium Inorganic materials 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 3
- 238000005303 weighing Methods 0.000 claims description 3
- 238000013461 design Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000002035 prolonged effect Effects 0.000 description 2
- 241000700605 Viruses Species 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000003245 working effect Effects 0.000 description 1
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R29/00—Arrangements for measuring or indicating electric quantities not covered by groups G01R19/00 - G01R27/00
- G01R29/08—Measuring electromagnetic field characteristics
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R33/00—Arrangements or instruments for measuring magnetic variables
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
- H04L63/0815—Network architectures or network communication protocols for network security for authentication of entities providing single-sign-on or federations
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/51—Discovery or management thereof, e.g. service location protocol [SLP] or web services
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- Computer Security & Cryptography (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Condensed Matter Physics & Semiconductors (AREA)
- Electromagnetism (AREA)
- Storage Device Security (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention relates to a big data security access control method, which comprises the following steps of operating a big data security access control system to control the big data security access, wherein the big data security access control system comprises: the request receiving equipment is arranged in the mobile terminal and used for receiving a login request instruction sent by a preset APP when a user inputs a user name and a login password to log in the preset APP running on the mobile terminal; and the hardware analysis equipment is used for accessing the current CPU model of the mobile terminal to obtain corresponding CPU model information when the login request instruction is received. The big data security access control system is safe, reliable and convenient to use.
Description
Technical Field
The invention relates to the field of network security, in particular to a big data security access control method.
Background
The network security refers to that the hardware, software and data in the system of the network system are protected and are not damaged, changed and leaked due to accidental or malicious reasons, the system continuously, reliably and normally operates, and the network service is not interrupted.
From the perspective of network operation and managers, it is desirable to protect and control the operations of accessing, reading and writing information of local network, avoid the threats of 'trapdoor', virus, illegal access, denial of service, illegal occupation and illegal control of network resources, and prevent and defend the attack of network hackers. For security and secrecy departments, the departments hope to filter and prevent the illegal, harmful or confidential information related to the country, avoid the leakage of confidential information, avoid the harm to the society and cause huge loss to the country.
Disclosure of Invention
According to an aspect of the present invention, there is provided a big data security access control method, the method including operating a big data security access control system to control big data security access, the big data security access control system including:
the request receiving equipment is arranged in the mobile terminal and used for receiving a login request instruction sent by a preset APP when a user inputs a user name and a login password to log in the preset APP running on the mobile terminal;
the hardware analysis equipment is arranged in the mobile terminal, is connected with the request receiving equipment and is used for accessing the current CPU model of the mobile terminal to obtain corresponding CPU model information when receiving the login request instruction;
the network access equipment is arranged on one side of the hardware analysis equipment and used for searching one or more CPU models bound with a user input user name from a network to be used as one or more safe CPU models when the login request instruction is received;
the data matching equipment is respectively connected with the hardware analysis equipment and the network access equipment and is used for matching the received CPU model information with the one or more safe CPU models, and when the safe CPU models are matched, an authorized login instruction is sent out, otherwise, a login prohibition instruction is sent out;
the leakage measuring equipment is respectively connected with the currently unused suspension pins of the network access equipment, the hardware analysis equipment and the data matching equipment so as to obtain a current electromagnetic leakage value of the currently unused suspension pins of the network access equipment, a current electromagnetic leakage value of the currently unused suspension pins of the hardware analysis equipment and a current electromagnetic leakage value of the currently unused suspension pins of the data matching equipment;
the CPLD device is connected with the leakage measuring equipment and is used for receiving a current electromagnetic leakage value of a currently unused suspension pin of the network access equipment, a current electromagnetic leakage value of a currently unused suspension pin of the hardware analysis equipment and a current electromagnetic leakage value of a currently unused suspension pin of the data matching equipment, and performing weighted mean operation on the current electromagnetic leakage value of the currently unused suspension pin of the network access equipment, the current electromagnetic leakage value of the currently unused suspension pin of the hardware analysis equipment and the current electromagnetic leakage value of the currently unused suspension pin of the data matching equipment to obtain a reference pin electromagnetic leakage value, and multiplying the obtained reference pin electromagnetic leakage value by a weighing factor to obtain a silicon wafer entity electromagnetic leakage value of the network access equipment;
the SD memory chip is used for pre-storing a current electromagnetic leakage value of a current unused suspension pin of the network access equipment, a current electromagnetic leakage value of a current unused suspension pin of the hardware analysis equipment and three weight values of the current electromagnetic leakage value of the current unused suspension pin of the data matching equipment which respectively participate in weighted mean calculation;
the gear adjusting device is respectively connected with the network access device and the CPLD device and is used for determining a corresponding down-regulation target gear according to a silicon wafer entity electromagnetic leakage value to realize the adjustment of a working gear of the network access device when the received silicon wafer entity electromagnetic leakage value exceeds a limit amount, wherein the larger the silicon wafer entity electromagnetic leakage value is, the lower the corresponding down-regulation target gear is;
in the SD memory chip, the current electromagnetic leakage value of the currently unused suspension pin of the network access device, the current electromagnetic leakage value of the currently unused suspension pin of the hardware analysis device and the current electromagnetic leakage value of the currently unused suspension pin of the data matching device are different in size, wherein the three weight values respectively participate in weighted mean calculation;
the speed adjusting device is further used for executing the downward adjustment executing operation of the current data processing speed of the network access device based on the operation speed downward adjustment multiple;
when the preset APP receives the login prohibition instruction, the static user accesses data related to the input user name of the static user;
the network access equipment searches one or more CPU models bound with a user input user name from a remote server of a preset APP supplier on the network to serve as one or more safe CPU models.
The invention has at least the following three important points:
(1) one or more CPU models bound with a user input user name are adopted as one or more safe CPU models to carry out access safety control on a preset APP;
(2) automatically distributing the current residual electric quantity according to the historical power consumption level of each device so as to effectively prolong the service time of each device;
(3) and carrying out targeted estimation on the electromagnetic leakage value of the silicon wafer entity of the equipment so as to adjust the working gear of the equipment based on the estimation result, thereby achieving balance between the working effect and the reduction of electromagnetic leakage.
The big data security access control system is safe, reliable and convenient to use. One or more CPU models bound with a user input user name are adopted to serve as one or more safe CPU models to carry out preset APP access safety control, and meanwhile, the current residual electric quantity is automatically distributed according to the historical power consumption level of each device, so that the service time of each device is effectively prolonged.
Drawings
Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a schematic diagram illustrating an arrangement of a mobile terminal interface APP in a big data security access control system according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Generally, app files are cracked patch files of certain software, namely files that can change unregistered software into registered software. The method for cracking by using the app generally comprises the following steps: the method comprises the steps of copying an app file carried by certain software together into a memory card through a data line or other modes by using a file management program (such as file power), installing a main program, opening file manager software such as FileMan software, finding the app file in the memory card, editing and copying the app file, finding system-apps in a software installation directory, editing and pasting the app file in a software folder, prompting whether the original file is covered or not, and completing decryption by selecting 'yes', namely covering the source file with the file, and completing decryption. Currently, APP is referred to as an application.
In the prior art, one or more CPU models bound with a user input user name cannot be adopted as one or more safe CPU models to perform preset APP access safety control, the current residual electric quantity cannot be automatically distributed according to the historical power consumption level of each device, the service time of each device is effectively prolonged, and the targeted estimation on the silicon wafer entity electromagnetic leakage value of the device cannot be performed.
In order to overcome the defects, the invention builds a big data security access control method, which comprises the step of operating a big data security access control system to control the big data security access, wherein the big data security access control system can effectively solve the corresponding technical problems.
Fig. 1 is a schematic diagram illustrating an arrangement of a mobile terminal interface APP in a big data security access control system according to an embodiment of the present invention.
The big data security access control system shown according to the embodiment of the invention comprises:
the request receiving equipment is arranged in the mobile terminal and used for receiving a login request instruction sent by a preset APP when a user inputs a user name and a login password to log in the preset APP running on the mobile terminal;
the hardware analysis equipment is arranged in the mobile terminal, is connected with the request receiving equipment and is used for accessing the current CPU model of the mobile terminal to obtain corresponding CPU model information when receiving the login request instruction;
the network access equipment is arranged on one side of the hardware analysis equipment and used for searching one or more CPU models bound with a user input user name from a network to be used as one or more safe CPU models when the login request instruction is received;
the data matching equipment is respectively connected with the hardware analysis equipment and the network access equipment and is used for matching the received CPU model information with the one or more safe CPU models, and when the safe CPU models are matched, an authorized login instruction is sent out, otherwise, a login prohibition instruction is sent out;
the leakage measuring equipment is respectively connected with the currently unused suspension pins of the network access equipment, the hardware analysis equipment and the data matching equipment so as to obtain a current electromagnetic leakage value of the currently unused suspension pins of the network access equipment, a current electromagnetic leakage value of the currently unused suspension pins of the hardware analysis equipment and a current electromagnetic leakage value of the currently unused suspension pins of the data matching equipment;
the CPLD device is connected with the leakage measuring equipment and is used for receiving a current electromagnetic leakage value of a currently unused suspension pin of the network access equipment, a current electromagnetic leakage value of a currently unused suspension pin of the hardware analysis equipment and a current electromagnetic leakage value of a currently unused suspension pin of the data matching equipment, and performing weighted mean operation on the current electromagnetic leakage value of the currently unused suspension pin of the network access equipment, the current electromagnetic leakage value of the currently unused suspension pin of the hardware analysis equipment and the current electromagnetic leakage value of the currently unused suspension pin of the data matching equipment to obtain a reference pin electromagnetic leakage value, and multiplying the obtained reference pin electromagnetic leakage value by a weighing factor to obtain a silicon wafer entity electromagnetic leakage value of the network access equipment;
the SD memory chip is used for pre-storing a current electromagnetic leakage value of a current unused suspension pin of the network access equipment, a current electromagnetic leakage value of a current unused suspension pin of the hardware analysis equipment and three weight values of the current electromagnetic leakage value of the current unused suspension pin of the data matching equipment which respectively participate in weighted mean calculation;
the gear adjusting device is respectively connected with the network access device and the CPLD device and is used for determining a corresponding down-regulation target gear according to a silicon wafer entity electromagnetic leakage value to realize the adjustment of a working gear of the network access device when the received silicon wafer entity electromagnetic leakage value exceeds a limit amount, wherein the larger the silicon wafer entity electromagnetic leakage value is, the lower the corresponding down-regulation target gear is;
in the SD memory chip, the current electromagnetic leakage value of the currently unused suspension pin of the network access device, the current electromagnetic leakage value of the currently unused suspension pin of the hardware analysis device and the current electromagnetic leakage value of the currently unused suspension pin of the data matching device are different in size, wherein the three weight values respectively participate in weighted mean calculation;
the speed adjusting device is further used for executing the downward adjustment executing operation of the current data processing speed of the network access device based on the operation speed downward adjustment multiple;
when the preset APP receives the login prohibition instruction, the static user accesses data related to the input user name of the static user;
the network access equipment searches one or more CPU models bound with a user input user name from a remote server of a preset APP supplier on the network to serve as one or more safe CPU models.
Next, a detailed description of the structure of the big data security access control system of the present invention will be further described.
In the big data security access control system:
the request receiving device, the hardware analysis device and the data matching device are respectively realized by adopting PAL chips with different models.
In the big data security access control system, the method further comprises:
and the electric quantity detection equipment is connected with the lithium battery and used for detecting the residual electric quantity of the lithium battery so as to output the residual electric quantity as real-time residual electric quantity.
In the big data security access control system, the method further comprises:
and the first power consumption counting device is connected with the network access device and used for counting the power consumption of the network access device in unit time based on the historical power consumption data of the network access device so as to output the power consumption as the power consumption in the first unit time.
In the big data security access control system, the method further comprises:
and the second power consumption statistical device is connected with the hardware analysis device and used for counting the power consumption of the hardware analysis device in unit time based on the historical power consumption data of the hardware analysis device to be output as the power consumption of the second unit time.
In the big data security access control system, the method further comprises:
and the electric quantity distribution equipment is respectively connected with the electric quantity detection equipment, the first power consumption statistic equipment and the second power consumption statistic equipment and is used for determining the electric quantity distributed to the network access equipment and the electric quantity distributed to the hardware analysis equipment based on the real-time residual electric quantity, the first unit time power consumption and the second unit time power consumption.
In the big data security access control system:
in the power distribution device, determining the amount of power distributed to the network access device and the amount of power distributed to the hardware analysis device based on the real-time residual power amount, the first unit time power consumption amount, and the second unit time power consumption amount includes: the higher the power consumption per unit time, the more power is allocated to the network access device.
In the big data security access control system:
in the power distribution device, determining the amount of power distributed to the network access device and the amount of power distributed to the hardware analysis device based on the real-time residual power amount, the first unit time power consumption amount, and the second unit time power consumption amount includes: the higher the power consumption per unit time, the more power is allocated to the hardware analysis device.
In the big data security access control system:
and when the preset APP receives the authorized login instruction, allowing the user to access data related to the input user name.
In addition, the CPLD has the characteristics of flexible programming, high integration level, short design and development period, wide application range, advanced development tool, low design and manufacturing cost, low requirement on hardware experience of designers, no need of testing for standard products, strong confidentiality, popular price and the like, and can realize large-scale circuit design, so that the CPLD is widely applied to prototype design and product production (generally less than 10,000) of products. CPLD devices are used in almost all applications where small-scale, general-purpose digital integrated circuits are used. The CPLD device has become an indispensable component of electronic products, and its design and application become a necessary skill for electronic engineers.
The CPLD is a digital integrated circuit in which a user constructs logic functions according to his or her own needs. The basic design method is to generate corresponding target files by means of an integrated development software platform and methods such as schematic diagrams, hardware description languages and the like, and to transmit codes to a target chip through a download cable (programming in the system) so as to realize the designed digital system.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (9)
1. A big data security access control method, the method comprising operating a big data security access control system to control big data security access, the big data security access control system comprising:
the request receiving equipment is arranged in the mobile terminal and used for receiving a login request instruction sent by a preset APP when a user inputs a user name and a login password to log in the preset APP running on the mobile terminal;
the hardware analysis equipment is arranged in the mobile terminal, is connected with the request receiving equipment and is used for accessing the current CPU model of the mobile terminal to obtain corresponding CPU model information when receiving the login request instruction;
the network access equipment is arranged on one side of the hardware analysis equipment and used for searching one or more CPU models bound with a user input user name from a network to be used as one or more safe CPU models when the login request instruction is received;
the data matching equipment is respectively connected with the hardware analysis equipment and the network access equipment and is used for matching the received CPU model information with the one or more safe CPU models, and when the safe CPU models are matched, an authorized login instruction is sent out, otherwise, a login prohibition instruction is sent out;
the leakage measuring equipment is respectively connected with the currently unused suspension pins of the network access equipment, the hardware analysis equipment and the data matching equipment so as to obtain a current electromagnetic leakage value of the currently unused suspension pins of the network access equipment, a current electromagnetic leakage value of the currently unused suspension pins of the hardware analysis equipment and a current electromagnetic leakage value of the currently unused suspension pins of the data matching equipment;
the CPLD device is connected with the leakage measuring equipment and is used for receiving a current electromagnetic leakage value of a currently unused suspension pin of the network access equipment, a current electromagnetic leakage value of a currently unused suspension pin of the hardware analysis equipment and a current electromagnetic leakage value of a currently unused suspension pin of the data matching equipment, and performing weighted mean operation on the current electromagnetic leakage value of the currently unused suspension pin of the network access equipment, the current electromagnetic leakage value of the currently unused suspension pin of the hardware analysis equipment and the current electromagnetic leakage value of the currently unused suspension pin of the data matching equipment to obtain a reference pin electromagnetic leakage value, and multiplying the obtained reference pin electromagnetic leakage value by a weighing factor to obtain a silicon wafer entity electromagnetic leakage value of the network access equipment;
the SD memory chip is used for pre-storing a current electromagnetic leakage value of a current unused suspension pin of the network access equipment, a current electromagnetic leakage value of a current unused suspension pin of the hardware analysis equipment and three weight values of the current electromagnetic leakage value of the current unused suspension pin of the data matching equipment which respectively participate in weighted mean calculation;
the gear adjusting device is respectively connected with the network access device and the CPLD device and is used for determining a corresponding down-regulation target gear according to a silicon wafer entity electromagnetic leakage value to realize the adjustment of a working gear of the network access device when the received silicon wafer entity electromagnetic leakage value exceeds a limit amount, wherein the larger the silicon wafer entity electromagnetic leakage value is, the lower the corresponding down-regulation target gear is;
in the SD memory chip, the current electromagnetic leakage value of the currently unused suspension pin of the network access device, the current electromagnetic leakage value of the currently unused suspension pin of the hardware analysis device and the current electromagnetic leakage value of the currently unused suspension pin of the data matching device are different in size, wherein the three weight values respectively participate in weighted mean calculation;
the speed adjusting device is further used for executing the downward adjustment executing operation of the current data processing speed of the network access device based on the operation speed downward adjustment multiple;
when the preset APP receives the login prohibition instruction, the static user accesses data related to the input user name of the static user;
the network access equipment searches one or more CPU models bound with a user input user name from a remote server of a preset APP supplier on the network to serve as one or more safe CPU models.
2. The method of claim 1, wherein:
the request receiving device, the hardware analysis device and the data matching device are respectively realized by adopting PAL chips with different models.
3. The method of claim 2, wherein the system further comprises:
and the electric quantity detection equipment is connected with the lithium battery and used for detecting the residual electric quantity of the lithium battery so as to output the residual electric quantity as real-time residual electric quantity.
4. The method of claim 3, wherein the system further comprises:
and the first power consumption counting device is connected with the network access device and used for counting the power consumption of the network access device in unit time based on the historical power consumption data of the network access device so as to output the power consumption as the power consumption in the first unit time.
5. The method of claim 4, wherein the system further comprises:
and the second power consumption statistical device is connected with the hardware analysis device and used for counting the power consumption of the hardware analysis device in unit time based on the historical power consumption data of the hardware analysis device to be output as the power consumption of the second unit time.
6. The method of claim 5, wherein the system further comprises:
and the electric quantity distribution equipment is respectively connected with the electric quantity detection equipment, the first power consumption statistic equipment and the second power consumption statistic equipment and is used for determining the electric quantity distributed to the network access equipment and the electric quantity distributed to the hardware analysis equipment based on the real-time residual electric quantity, the first unit time power consumption and the second unit time power consumption.
7. The method of claim 6, wherein:
in the power distribution device, determining the amount of power distributed to the network access device and the amount of power distributed to the hardware analysis device based on the real-time residual power amount, the first unit time power consumption amount, and the second unit time power consumption amount includes: the higher the power consumption per unit time, the more power is allocated to the network access device.
8. The method of claim 7, wherein:
in the power distribution device, determining the amount of power distributed to the network access device and the amount of power distributed to the hardware analysis device based on the real-time residual power amount, the first unit time power consumption amount, and the second unit time power consumption amount includes: the higher the power consumption per unit time, the more power is allocated to the hardware analysis device.
9. The method of claim 8, wherein:
and when the preset APP receives the authorized login instruction, allowing the user to access data related to the input user name.
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2019
- 2019-01-07 CN CN201910025394.9A patent/CN110753025B/en active Active
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| CN103178484A (en) * | 2011-12-23 | 2013-06-26 | 比亚迪股份有限公司 | Mobile power source and mobile terminal using same |
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