CN115859331B - Smart city information security guarantee system - Google Patents
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- CN115859331B CN115859331B CN202211663082.9A CN202211663082A CN115859331B CN 115859331 B CN115859331 B CN 115859331B CN 202211663082 A CN202211663082 A CN 202211663082A CN 115859331 B CN115859331 B CN 115859331B
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- 230000035945 sensitivity Effects 0.000 claims description 8
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Abstract
The invention discloses a smart city information security guarantee system, which belongs to the technical field of information security guarantee, and can actively judge whether an original data set requested by a data user is matched with a smart city task required by the data user when the smart city is constructed, actively prompt an abnormal original data set request, strengthen the auditing and management supervision of the data user and avoid the abuse of the original data set by the data user; the method and the device have the characteristics of wide application range, high security value, more and more complex examination processes and longer examination period by utilizing the characteristic that the to-be-acquired original data set with large examination coefficients is utilized, and the data acquirers and the data consumers corresponding to the to-be-acquired original data set with large examination coefficients are preferentially examined when the related work of the to-be-acquired original data set is processed, so that the problems that the examination flow of the to-be-acquired original data set is prolonged and the construction progress of a smart city is influenced can be avoided.
Description
Technical Field
The invention belongs to the technical field of information security, and particularly relates to a smart city information security system.
Background
Along with the promotion of urbanization, the introduction of smart cities can promote the utilization efficiency of urban resources, optimize urban management and service, and improve the living standard of residents.
In the actual operation process, because the project quantity related to the construction of the smart city is large, the related work is more, and in the actual operation process, social enterprises and research institutions are also required to be introduced into the system, so that a part of data is required to be opened by government institutions to be used for the social enterprises and the research institutions, the public institutions are encouraged to innovate according to the opened data to create larger value, but the data outflow is caused, the illegal use of the data and the abuse risk are greatly improved, in addition, in order to avoid the abuse of the opened data, the data with larger confidentiality requirement and wide use range are required to be enhanced, the auditing period is longer, the difficulty is prolonged, and the construction progress of the smart city is also caused.
Disclosure of Invention
The invention aims to provide a smart city information security guarantee system, which solves the problems that released city data are illegally used and abused in the prior art when smart city construction is carried out.
The aim of the invention can be achieved by the following technical scheme:
a smart city information security system, comprising:
the data storage module is used for storing the original data set;
the auditing module is used for auditing the data acquisition party of the original data set to be acquired and the data use party corresponding to the original data set to be acquired;
the working method of the intelligent city information security guarantee system comprises the following steps:
the method comprises the steps that firstly, when a smart city task is executed, a data set corresponding to the smart city task is obtained, wherein the data set comprises a plurality of original data sets;
secondly, classifying the smart city tasks, and classifying the smart city tasks meeting the same purpose into the same task group;
in the same task group, acquiring the number n of the smart city tasks, simultaneously acquiring the number R of corresponding occurrences of each group of original data in the task group in the smart city tasks, and calculating according to a formula R=r/n to obtain a correlation coefficient R of each original data group corresponding to the task group;
thirdly, when a city is required to be built, acquiring a required smart city task, and taking the execution unit as a data user;
the data user initiates an original data acquisition request to the data palm control party according to the required smart city task, wherein the original data acquisition request comprises an original data set required by executing the corresponding smart city task;
acquiring a correlation coefficient R of an original data set requested to be acquired by a data user in a corresponding smart city task, and considering the corresponding original data set as a reasonable request data set when R is less than or equal to alpha;
when R > alpha is established, the corresponding original data set is considered as an abnormal request data set;
wherein α is a preset coefficient value.
As a further scheme of the invention, the invention also comprises an alarm module;
the alarm module is used for marking the abnormal request data set and sending alarm information to prompt the data palm control party to audit the abnormal data set;
when the original data acquisition request sent by the data user comprises an abnormal request data set, the alarm module marks the abnormal request data set and reminds a data palm control party.
As a further scheme of the present invention, in the third step, the original data set stored in the data storage module is compared with the original data set included in the original data acquisition request sent by each data user, and the original data set which does not exist in the data storage module is marked as the original data set to be acquired;
acquiring correlation coefficients R of an original data group to be acquired corresponding to different task groups in an original data acquisition request range sent by a data user, and summing and calculating to obtain a universal coefficient U corresponding to the original data;
acquiring a universal coefficient U of each group of original data;
acquiring a sensitivity coefficient X and a universal coefficient U of each original data set to be acquired;
calculating to obtain an auditing coefficient H of each original data group to be acquired according to a formula H=γ 1*X +γ 2*U;
wherein γ1 and γ2 are preset coefficients.
And sequencing the original data sets to be acquired according to the order of the auditing coefficient H from large to small, transmitting the order of the original data sets to an auditing module, and auditing the data acquirers and the data users corresponding to the original data sets to be acquired by the auditing module according to the order.
As a further scheme of the invention, the method for calculating the sensitivity coefficient X comprises the following steps:
acquiring the number of times c1 of attack of an original data set and the number of times c2 of attack of a data set corresponding to each smart city task, and calculating according to a formula G=c1+c2/v to obtain a sensitive value G of the corresponding original data set;
the c1 and the c2 are the total times of attack of the corresponding original data set and the data set corresponding to the smart city task respectively;
calculating to obtain a mutation value G of the corresponding original data set according to a formula g=g/T, wherein T is a preset time value;
and calculating a sensitivity coefficient X of the corresponding original data set according to a formula X=G G/beta 1, wherein beta 1 is a preset coefficient.
As a further aspect of the present invention, the value of T is seven days.
The invention has the beneficial effects that:
(1) When the smart city construction is carried out, the corresponding original data required by processing the smart city tasks in the prior art is obtained, so that the necessity of each original data set for one smart city task is judged in the subsequent process, whether the original data set requested by the data user is matched with the smart city tasks required by the data user or not is actively judged, and abnormal original data set requests are actively prompted, so that the auditing and management supervision of the data user are enhanced, and the data user is prevented from abusing the original data set;
(2) The method has the characteristics of wide application range and high confidentiality value, so that the potential risk is larger after the method is opened, more and more complex examination processes and longer examination periods are realized.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic diagram of a framework structure of a smart city information security system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
A smart city information security system, as shown in fig. 1, comprising:
the data storage module is used for storing the original data set;
the alarm module is used for marking the abnormal request data set and sending alarm information to prompt the data palm control party to audit the abnormal data set;
the auditing module is used for auditing an acquisition party of the original data set to be acquired and a data user corresponding to the original data set to be acquired, so that the problems of inconsistent qualification of the acquisition party, low acquisition efficiency, poor acquisition result quality, inconsistent qualification of the data user and the like of the original data set to be acquired are avoided;
the data processing module is used for processing and analyzing the original data sets in the data storage module, judging whether each original data set belongs to a reasonable request data set or an abnormal request data set, and calculating an audit coefficient H of each original data set;
the working method of the intelligent city information security guarantee system comprises the following steps:
the method comprises the steps that firstly, when a smart city task is executed, a data set corresponding to the smart city task is obtained, wherein the data set comprises a plurality of original data sets;
the smart city task refers to a process of processing a large amount of original data when a certain purpose needs to be met in order to construct a smart city;
the original data group contains the distribution of a data corresponding to the same object in a certain time or a certain space;
secondly, classifying the smart city tasks, and classifying the smart city tasks meeting the same purpose into the same task group;
in the same task group, acquiring the number n of the smart city tasks, simultaneously acquiring the number R of corresponding occurrences of each group of original data in the task group in the smart city tasks, and calculating according to a formula R=r/n to obtain a correlation coefficient R of each original data group corresponding to the task group;
in the first step and the second step, corresponding original data required by processing the smart city task in the prior art is obtained by analyzing the historical data, so that the necessity of each original data set for one smart city task can be judged;
thirdly, calculating to obtain a sensitivity coefficient X of each original data set;
the calculating method of the sensitivity coefficient X comprises the following steps:
acquiring the number of times c1 of attack of an original data set and the number of times c2 of attack of a data set corresponding to each smart city task, and calculating according to a formula G=c1+c2/v to obtain a sensitive value G of the corresponding original data set;
the c1 and the c2 are the total times of attack of the corresponding original data set and the data set corresponding to the smart city task respectively;
calculating according to a formula g=g/T to obtain a mutation value G of the corresponding original data set, wherein T is a preset time value, and in one embodiment of the invention, the value of T is seven days a week;
calculating a sensitivity coefficient X of a corresponding original data set according to a formula X=G G/beta 1, wherein beta 1 is a preset coefficient;
because part of the original data sets have larger hidden value, uncontrollable transmission of the original data sets has larger potential safety hazard, the data can be attacked in the normal course of transmission and use, and the importance of a group of data can be reflected to a certain extent.
Fourth, when the city needs to be built in the smart city, obtaining the smart city tasks which need to be built in the city, obtaining execution units of the smart city tasks according to modes such as bidding, and taking the execution units as data users;
the data user initiates an original data acquisition request to the data palm control party according to the required smart city task, wherein the original data acquisition request comprises an original data set required by executing the corresponding smart city task;
acquiring a correlation coefficient R of an original data set requested to be acquired by a data user in a corresponding smart city task, and considering the corresponding original data set as a reasonable request data set when R is less than or equal to alpha;
when R > alpha is established, the corresponding original data set is considered as an abnormal request data set;
when an original data acquisition request sent by a data user comprises an abnormal request data set, an alarm module marks the abnormal request data set and reminds a data palm control party to audit the abnormal request data set;
wherein alpha is a preset coefficient value;
fifthly, comparing the original data set stored in the data storage module with the original data set contained in the original data acquisition request sent by each data user, and marking the original data set which does not exist in the data storage module as the original data set to be acquired;
acquiring correlation coefficients R of an original data group to be acquired corresponding to different task groups in an original data acquisition request range sent by a data user, and summing and calculating to obtain a universal coefficient U corresponding to the original data;
acquiring a universal coefficient U of each group of original data;
acquiring a sensitivity coefficient X and a universal coefficient U of each original data set to be acquired;
calculating to obtain an auditing coefficient H of each original data group to be acquired according to a formula H=γ 1*X +γ 2*U;
wherein γ1 and γ2 are preset coefficients;
for each original data set to be acquired, sequencing the original data sets to be acquired according to the sequence of the auditing coefficient H from large to small, transmitting the sequence of the original data sets to an auditing module, and auditing the data acquirers and the data consumers corresponding to the original data sets to be acquired by the auditing module according to the sequence;
for an original data set to be acquired, an appropriate unit is required to acquire the original data set to be acquired, the unit for acquiring the original data set to be acquired is called a data acquisition party, and the data acquisition party can be mutually overlapped with or mutually independent of a data use party;
the original data set to be acquired with the large auditing coefficient H has the characteristics of wide application range and high confidentiality value, so that the potential risk is larger after the original data set is opened, more and more complex auditing processes are provided, when related work of the original data set to be acquired is processed, the data acquirers and the data users corresponding to the original data set to be acquired with the large auditing coefficient H are preferentially audited, and the problems that the auditing flow of the whole related original data set to be acquired is prolonged and the construction progress of a smart city is influenced can be avoided.
When the smart city construction is carried out, the method and the system can actively judge whether the original data set requested by the data user is matched with the smart city task required by the data user, actively prompt the abnormal original data set request and avoid the data user abusing the original data set.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely illustrative and explanatory of the invention, as various modifications and additions may be made to the particular embodiments described, or in a similar manner, by those skilled in the art, without departing from the scope of the invention or exceeding the scope of the invention as defined in the claims.
Claims (3)
1. A smart city information security system, comprising:
the data storage module is used for storing the original data set;
the auditing module is used for auditing the data acquisition party of the original data set to be acquired and the data use party corresponding to the original data set to be acquired;
the working method of the intelligent city information security guarantee system comprises the following steps:
the method comprises the steps that firstly, when a smart city task is executed, a data set corresponding to the smart city task is obtained, wherein the data set comprises a plurality of original data sets;
secondly, classifying the smart city tasks, and classifying the smart city tasks meeting the same purpose into the same task group;
in the same task group, acquiring the number n of the smart city tasks, simultaneously acquiring the number R of corresponding occurrences of each group of original data in the task group in the smart city tasks, and calculating according to a formula R=r/n to obtain a correlation coefficient R of each original data group corresponding to the task group;
thirdly, when a city is in need of smart city construction, acquiring smart city tasks which need to be carried out, acquiring execution units of all the smart city tasks, and taking the corresponding execution units as data users;
the data user initiates an original data acquisition request to the data palm control party according to the required smart city task, wherein the original data acquisition request comprises an original data set required by executing the corresponding smart city task;
acquiring a correlation coefficient R of an original data set requested to be acquired by a data user in a corresponding smart city task, and considering the corresponding original data set as a reasonable request data set when R is less than or equal to alpha;
when R > alpha is established, the corresponding original data set is considered as an abnormal request data set;
wherein α is a preset coefficient value.
2. The smart city information security system of claim 1, further comprising an alarm module;
the alarm module is used for marking the abnormal request data set and sending alarm information to prompt the data palm control party to audit the abnormal data set;
when the original data acquisition request sent by the data user comprises an abnormal request data set, the alarm module marks the abnormal request data set and reminds a data palm control party.
3. The smart city information security system of claim 1, wherein in the third step, the original data set stored in the data storage module is compared with the original data set included in the original data acquisition request sent by each data user, and the original data set not existing in the data storage module is marked as the original data set to be acquired;
acquiring correlation coefficients R of an original data group to be acquired corresponding to different task groups in an original data acquisition request range sent by a data user, and summing and calculating to obtain a universal coefficient U corresponding to the original data;
acquiring a universal coefficient U of each group of original data;
acquiring a sensitivity coefficient X and a universal coefficient U of each original data set to be acquired;
calculating to obtain an auditing coefficient H of each original data group to be acquired according to a formula H=γ 1*X +γ 2*U;
wherein γ1 and γ2 are preset coefficients;
and sequencing the original data sets to be acquired according to the order of the auditing coefficient H from large to small, transmitting the order of the original data sets to an auditing module, and auditing the data acquirers and the data users corresponding to the original data sets to be acquired by the auditing module according to the order.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018036324A1 (en) * | 2016-08-26 | 2018-03-01 | 中兴通讯股份有限公司 | Smart city information sharing method and device |
| CN112232997A (en) * | 2020-04-29 | 2021-01-15 | 广元量知汇科技有限公司 | User request data processing method for smart city |
| CN112532705A (en) * | 2020-11-20 | 2021-03-19 | 季速漫 | Smart city service system based on big data |
| CN115293599A (en) * | 2022-08-10 | 2022-11-04 | 成都西南锦云大数据有限公司 | Big data acquisition of wisdom city system that gathers |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106302683A (en) * | 2016-08-10 | 2017-01-04 | 成都秦川科技发展有限公司 | Smart city system |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018036324A1 (en) * | 2016-08-26 | 2018-03-01 | 中兴通讯股份有限公司 | Smart city information sharing method and device |
| CN112232997A (en) * | 2020-04-29 | 2021-01-15 | 广元量知汇科技有限公司 | User request data processing method for smart city |
| CN112532705A (en) * | 2020-11-20 | 2021-03-19 | 季速漫 | Smart city service system based on big data |
| CN115293599A (en) * | 2022-08-10 | 2022-11-04 | 成都西南锦云大数据有限公司 | Big data acquisition of wisdom city system that gathers |
Non-Patent Citations (1)
| Title |
|---|
| 智慧城市云平台安全保护体系研究;肖静 等;现代计算机(第14期);第51-56页 * |
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