Mobile data destruction system

Abstract

The invention relates to the technical field of electric data processing, in particular to a mobile data destruction system. The system is provided with a breakdown control module for controlling voltage and current output by a high-voltage breakdown module. The electric data in the historical destruction process are analyzed, and the electric data fluctuation in the historical destruction process and the data fluctuation at the same moment among different historical destruction processes are effectively analyzed by constructing the electric data matrix. And further analyzing the response characteristic correlation under the two dimensions of voltage and current, and obtaining an adjustment coefficient to adjust the voltage and current output by the high-voltage breakdown module. By analyzing the stability characteristics of the electric data in the historical destruction process, the adjustment coefficient is set, synchronous stability of voltage and current is guaranteed, and then stable and effective breakdown voltage is output for data destruction.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic data processing, and in particular to a mobile data destruction system. Background Art

[0002] In the digital age, the importance of data security has become increasingly prominent. Mobile data destruction, as a key means to ensure data security, has received widespread attention. Its core is to use portable devices to destroy the storage medium through physical means, so that the storage medium completely loses its storage capacity, thereby ensuring that the data stored in the system is permanently lost and effectively preventing data leakage. At present, high-voltage breakdown is a common mobile data destruction method. Its principle is to use high voltage to destroy the storage unit. This process will cause irreversible damage to the memory, making the corresponding motherboard unusable. This method cleverly uses the characteristics of high-voltage breakdown causing irreversible damage to the motherboard storage unit to achieve complete destruction of data. However, to ensure that the data is completely destroyed, a stable breakdown voltage is a key factor. Only by maintaining a stable breakdown voltage can the integrity of data destruction be guaranteed and the risk of data leakage be eliminated.

[0003] However, in actual application scenarios, the situation is often more complicated. On the one hand, the types of devices to be destroyed are diverse, including hard disks, USB flash drives, mobile phones, tablet computers, etc., which have significant differences in interface specifications, circuit design, storage principles, etc. On the other hand, the use environment is also extremely complex, which may involve harsh conditions such as high temperature, humidity, and electromagnetic interference. The combined effect of these factors makes it very easy for the voltage or current to become unstable during the high-voltage breakdown process, which in turn leads to incomplete data destruction. Most of the existing mobile data destruction methods rely on high-voltage generators and corresponding switching devices. However, there is a common defect in such methods, that is, in actual operation, the interference that may be caused by factors such as device type, contact method, and environment is often ignored. When faced with the task of destroying a large number of devices, the phenomenon of unstable breakdown voltage will frequently occur. Once the breakdown voltage is unstable, the data of some devices to be destroyed cannot be completely destroyed, leaving serious data leakage risks. Summary of the invention

[0004] In order to solve the technical problem that the electrical data released by the mobile destruction system is unstable when the data storage medium is broken, the purpose of the present invention is to provide a mobile data destruction system, and the technical solution adopted is as follows:

[0005] The present invention proposes a mobile data destruction system, the system comprising:

[0006] A high-voltage breakdown module is used to execute a data destruction command and perform a high-voltage breakdown on a data storage medium;

[0007] The breakdown control module includes a data storage unit, a data processing unit, and a control unit;

[0008] The data storage unit is used to store the electrical data sequences in each historical destruction process. The electrical data includes two dimensions: voltage and current. All the electrical data sequences in each dimension are arranged to form an electrical data matrix corresponding to that dimension;

[0009] The data processing unit is used to obtain the disorder influence eigenvalue of each electrical data sequence according to the data volatility of the electrical data sequence itself and the differences between the electrical data sequences in different historical destruction processes; fuse the disorder influence eigenvalue and the electrical data matrix to obtain a feature sequence; obtain the deviation sequence of the electrical data matrix according to the data difference between the electrical data sequence and the standard breakdown electrical data, and fuse the deviation sequence and the feature sequence to obtain the interference eigenvalue sequences in two electrical data dimensions;

[0010] The control unit is used to obtain an adjustment coefficient according to the correlation of the interference eigenvalue sequences in two electrical data dimensions, and adjust the voltage and current output by the high-voltage breakdown module based on the adjustment coefficient.

[0011] Further, the data volatility is the coefficient of variation of the electrical data sequence.

[0012] Further, the difference between the electrical data sequences in different historical destruction processes is the DTW distance between the electrical data sequences.

[0013] Further, the obtaining of the disorder influence eigenvalue of each electrical data sequence includes:

[0014] For each historical destruction process, the average difference between the electrical data sequences between the historical destruction process and all other historical destruction processes is used as the overall difference; the product of the overall difference and the data volatility is normalized to obtain the disorder influence eigenvalue of the corresponding electrical data sequence.

[0015] Further, the obtaining method of the feature sequence includes:

[0016] The electrical data sequence is used as a column in the electrical data matrix; the disorder influence eigenvalues corresponding to each historical destruction process form a disorder influence eigenvalue sequence, and the transposed matrix of the disorder influence eigenvalue sequence is multiplied by the electrical data matrix through matrix multiplication to obtain the feature sequence.

[0017] Further, the obtaining method of the deviation sequence includes:

[0018] Obtain the data difference between each element in the electrical data matrix and the standard breakdown electrical data, and construct a deviation matrix; in the deviation matrix, average the data differences at the same moment in different historical destruction processes to obtain the average data difference at each moment, and form the deviation sequence.

[0019] Further, the method for obtaining the interference eigenvalue sequence includes:

[0020] Use the sum value of the deviation sequence and the feature sequence as the interference eigenvalue sequence.

[0021] Further, the correlation is the absolute value of the Pearson correlation coefficient between the interference eigenvalue sequences in two electrical data dimensions.

[0022] Further, the method for obtaining the adjustment coefficient includes:

[0023] Perform a negative correlation mapping and normalization on the correlation to obtain an interference weight; use the decay curve method in the PI control method to obtain a proportional parameter, take the product of the proportional parameter and the interference weight as the parameter adjustment amount, and take the sum value of the proportional parameter and the parameter adjustment amount as the adjustment coefficient.

[0024] Further, each time a destruction process is executed, the data storage unit needs to update the historical destruction process data, and the number of historical destruction processes stored in the data storage unit remains unchanged.

[0025] The present invention has the following beneficial effects:

[0026] In order to avoid fluctuations in the breakdown electrical data output by the mobile data destruction system, the present invention sets up a breakdown control module to control the voltage and current output by the high-voltage breakdown module. The present invention analyzes the electrical data in the historical destruction process, and effectively analyzes the electrical data fluctuations in the historical destruction process and the data fluctuations at the same moment between different historical destruction processes by constructing an electrical data matrix. The final interference eigenvalue sequence is determined through two-dimensional analysis. Each element in the interference eigenvalue sequence represents the actual response result of being interfered by the environment in the corresponding dimension under the actual destruction process based on the existing feedback control parameters. Further analyze the correlation of the response characteristics in the two dimensions of voltage and current. If the characteristics of the two are significantly correlated, it means that the control parameters in the destruction system are appropriate and do not need to be adjusted too much. Therefore, an adjustment coefficient can be obtained to adjust the voltage and current output by the high-voltage breakdown module, ensure the synchronous stability of the voltage and current, and then output a stable and effective breakdown voltage for data destruction. Description of the Drawings

[0027] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0028] Figure 1 A block diagram of a mobile data destruction system provided by an embodiment of the present invention;

[0029] Figure 2 A schematic diagram of the modules of a mobile data destruction device provided by an embodiment of the present invention. Detailed implementation manners

[0030] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of a mobile data destruction system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0032] Please refer to Figure 2, which shows a schematic diagram of a mobile data destruction device module provided by an embodiment of the present invention. The device mainly includes a high-voltage transformer module, a high-voltage switch, a power switch, a control chip, a battery pack, a battery level indicator, and a charging interface. The battery pack is composed of multiple rechargeable battery units. When the system needs power supply, the battery pack outputs the stored electrical energy to the high-voltage transformer and the control chip in the form of a stable low voltage; the high-voltage transformer works according to the law of electromagnetic induction. After the system starts, the low voltage from the battery pack is connected to the primary winding of the high-voltage transformer, and the control chip issues an instruction to make the current pass through the primary winding stably. Under the action of the iron core, the secondary winding induces a high voltage of 30 KV and outputs a low current of 0.1 mA to perform the high-voltage breakdown operation on the device to be destroyed; the battery level indicator is composed of multiple light-emitting diodes and is used to display the remaining battery level information of the battery pack; the charging interface is used to connect to an external charging device to replenish electrical energy for the battery pack; the power switch is a control component for turning on and off the system power supply and can start and stop the system; the high-voltage switch realizes the energization of the high-voltage output according to the signal sent by the control chip; the control chip integrates a microprocessor, sensors, a storage unit, and various control power supplies inside. The control chip collects the state information of each component of the system through sensors, including but not limited to the battery pack power and the high-voltage transformer output parameters, to achieve precise control and complete data destruction. An embodiment of the present invention proposes a mobile data destruction system, which is an improvement of some modules based on this device. The following specifically describes the specific solution of a mobile data destruction system provided by the present invention with reference to the accompanying drawings.

[0033] Please refer to Figure 1 , which shows a block diagram of a mobile data destruction system provided by an embodiment of the present invention. The system mainly includes a high-voltage breakdown module 101 and a breakdown control module 102. Among them, the breakdown control module can feedback control commands to the high-voltage breakdown module. The breakdown control module 102 also includes three units: a data storage unit 201, a data processing unit 202, and a control unit 203.

[0034] The data storage unit 201 is used to store the electrical data sequences in each historical destruction process. That is, each data destruction process will generate a series of voltage data and current data in time series. The data in these two dimensions form two electrical data sequences. In order to analyze the data fluctuation impact in the destruction process, an embodiment of the present invention jointly analyzes the electrical data sequences of multiple historical destruction processes and forms an electrical data matrix corresponding to the dimension through arrangement, that is, there is an electrical data matrix in the voltage dimension and an electrical data matrix in the current dimension.

[0035] It should be noted that the data analysis methods of the electrical data matrices in the two dimensions in the subsequent units are the same. Therefore, in the subsequent description of an embodiment of the present invention, the processing methods of the two electrical data matrices will not be described in detail, and only the electrical data matrix in the voltage dimension will be used as an example for illustration.

[0036] It should be noted that after obtaining the electrical data sequence, methods such as filtering and noise reduction can be used to reduce the influence of noise information in the data. In the embodiments of the present invention, the electrical data sequence of each historical destruction process is used as a column of the electrical data matrix and arranged in the order of the historical destruction process.

[0037] In the actual data destruction operation process, it can be found that after multiple destructions, due to problems with the hardware of the destruction device, there will be a phenomenon that the subsequent data storage medium is not completely destroyed. Since various complex interference factors may affect the execution of the destruction operation, after a period of destruction operation, the output parameters of the high-voltage transformer will fluctuate, resulting in the inability to maintain a stable high voltage during the high-voltage breakdown process. Therefore, it is necessary to perform volatility analysis on the historical data, and then determine the influence of the change characteristics of the historical data on the control parameters of the subsequent destruction process, and then perform feedback adjustment. Therefore, the data processing unit 202 is mainly used to analyze the fluctuations of the horizontal and vertical data in the electrical data matrix, and then determine the feedback influence in the subsequent destruction process.

[0038] The data processing unit 202 first analyzes the data volatility of the electrical data sequence itself. The greater the data volatility, the more unstable the situation exists during this destruction process. Further determine the differences between the electrical data sequences of different historical destruction processes. If the destruction system can output stable electrical data, the electrical data sequences between different destruction processes should have similar characteristics. Therefore, the greater the difference between the electrical data sequences, the more obvious the unstable output during consecutive multiple historical destruction processes. By combining these two characteristics, the disorder influence eigenvalue of each electrical data sequence can be obtained. That is, the disorder influence eigenvalue represents the degree of system disorder under a destruction process. The greater the disorder influence eigenvalue, the greater the degree of interference influence during this destruction process.

[0039] Furthermore, in order to combine the interference influence degree and the specific electrical data of different historical destruction processes in the actual destruction process, and in order to accurately reflect the data characteristics in the actual destruction process, the data processing unit 202 fuses the disorder influence eigenvalue with the electrical data matrix to obtain a feature sequence.

[0040] Further considering that the electrical data during the destruction process should be stable and rated standard electrical data, the greater the data difference between the standard breakdown electrical data indicates that the destruction process is more unstable. Therefore, further, according to the data difference between the data sequence and the standard breakdown electrical data, the deviation sequence of the electrical data matrix can be obtained, where each element in the deviation sequence represents the deviation information of a historical destruction process, and then by fusing with the feature sequence, the interference eigenvalue sequence under two electrical data dimensions can be obtained. The interference eigenvalue sequence integrates the original electrical data information, fluctuation information, and deviation information, and can represent the corresponding data characteristics in the actual destruction process under the control parameters of the system for all historical destruction processes.

[0041] For the data destruction process, the stability of the electrical data represents the stability in two dimensions of voltage data and current data. Therefore, the correlation between the voltage and current change characteristics should be further analyzed. If there is an obvious lack of correlation, it indicates that the control parameters set by using feedback control in the actual control process cannot respond in a timely and effective manner, and additional adjustment of the electrical data is required to ensure the stability of the breakdown voltage and breakdown current. Therefore, the control unit 203 obtains the adjustment coefficient according to the correlation of the interference eigenvalue sequences under two electrical data dimensions, and adjusts the voltage and current output by the high-voltage breakdown module based on the adjustment coefficient.

[0042] Preferably, in the embodiment of the present invention, the data storage unit further has the function of data update. Each time a destruction process is executed, the data storage unit needs to update the historical destruction process data, and the number of historical destruction processes stored in the data storage unit remains unchanged. In the embodiment of the present invention, based on the storage capacity of the data storage unit, it is set to store the data of 50 historical destruction processes in total. Each time a new destruction process is executed, the earliest destruction process among the 50 times is removed, and the data of the latest destruction process is supplemented.

[0043] Preferably, in the embodiment of the present invention, the method for obtaining the data volatility of the electrical data sequence itself in the data processing unit is: using the coefficient of variation of the electrical data sequence as the data volatility. The greater the coefficient of variation, the greater the fluctuation of the elements in the sequence and the more unstable the data. The method for obtaining the coefficient of variation is a well-known technical means for those skilled in the art and will not be elaborated here.

[0044] Preferably, in the embodiment of the present invention, since the electrical data sequences of different historical destruction processes are all time series sequences, the dynamic time warping algorithm can be used to obtain the DTW distance between the sequences as the difference between the sequences. It should be noted that because there are multiple historical destruction processes, for a historical destruction process, it is necessary to calculate the difference in the electrical data sequences between this historical destruction process and each other historical destruction process.

[0045] Preferably, in the embodiment of the present invention, the method for obtaining the disorder influence eigenvalue includes:

[0046] For each historical destruction process, the average difference in the electrical data sequence between the historical destruction process and all other historical destruction processes is taken as the overall difference. The product of the overall difference and the data volatility is normalized to obtain the disorder influence eigenvalue corresponding to the electrical data sequence. That is, in the embodiments of the present invention, the overall difference and the data volatility are positively correlated and fused in the form of a product. The greater the overall difference and the greater the data volatility, the more unstable the electrical data of the historical destruction process, and the greater the disorder influence eigenvalue.

[0047] It should be noted that the normalization process in the embodiments of the present invention uses the method of softmax function mapping. In other embodiments, other function mappings or range normalization and other methods can also be used for implementation, which will not be elaborated here.

[0048] Preferably, in the embodiments of the present invention, the method for obtaining the feature sequence includes:

[0049] Since the electrical data sequence in the embodiments of the present invention is a column in the electrical data matrix, the disorder influence eigenvalues corresponding to each historical destruction process constitute a disorder influence eigenvalue sequence. The transposed matrix of the disorder influence eigenvalue sequence is multiplied by the electrical data matrix through matrix multiplication to obtain the feature sequence. The disorder influence eigenvalue and the electrical data matrix can be effectively fused through basic operations of linear algebra.

[0050] Preferably, in the embodiments of the present invention, the method for obtaining the deviation sequence includes:

[0051] The data difference between each element in the electrical data matrix and the standard breakdown electrical data is obtained, and a deviation matrix is constructed. It should be noted that the data difference in the embodiments of the present invention is the absolute value of the difference.

[0052] In the deviation matrix, the average of the data differences at the same moment of different historical destruction processes is obtained, and the average data difference at each moment is obtained, constituting the deviation sequence.

[0053] In the embodiments of the present invention, the standard voltage of the standard electrical data is 30 KV, and the standard current is 0.1 mA.

[0054] Preferably, in the embodiments of the present invention, the method for obtaining the interference eigenvalue sequence includes:

[0055] Since the lengths of the deviation sequence and the feature sequence are the same, both being the time series length of the electrical data sequence, the sum value of the deviation sequence and the feature sequence can be directly used as the interference eigenvalue sequence.

[0056] Preferably, in the embodiments of the present invention, the correlation is the absolute value of the Pearson correlation coefficient between the interference eigenvalue sequences under two electrical data dimensions. The larger the absolute value of the Pearson correlation coefficient, the more linearly correlated the interference eigenvalue sequences under the two dimensions are, that is, the more they have the same change characteristics.

[0057] Preferably, in the embodiments of the present invention, the method for obtaining the adjustment coefficient includes:

[0058] Perform a negative correlation mapping and normalization on the correlation to obtain an interference weight. The stronger the correlation, the stronger the stability of the synchronization of the voltage and current under the actual feedback control, which indicates that the response difference to interference under the current control parameters is smaller, and the adjustment amplitude of the corresponding proportional parameter is smaller; if the correlation of the synchronous stable change of the voltage and current under the influence of interference in the actual response control process is weaker, it indicates that the response difference to interference under the current control parameters is larger, and the adjustment amplitude of the corresponding proportional parameter is larger. Therefore, it is necessary to perform a negative correlation mapping and normalization on the correlation to obtain an interference weight with a value range between 0 and 1. It should be noted that in an embodiment of the present invention, since the correlation is the absolute value of the Pearson coefficient and its value range is already between 0 and 1, the interference weight can be directly obtained by subtracting the correlation from the positive integer 1.

[0059] Use the decay curve method in the PI control method to obtain the proportional parameter, that is, this proportional parameter is an initial parameter, and the interference weight also needs to be combined. Therefore, the product of the proportional parameter and the interference weight is used as the parameter adjustment amount, and the sum of the proportional parameter and the parameter adjustment amount is used as the adjustment coefficient.

[0060] In summary, the embodiments of the present invention set up a breakdown control module to control the voltage and current output by the high-voltage breakdown module. Analyze the electrical data in the historical destruction process, and effectively analyze the electrical data fluctuations in the historical destruction process and the data fluctuations at the same moment between different historical destruction processes by constructing an electrical data matrix. Further analyze the correlation of the response characteristics under the two dimensions of voltage and current, and obtain an adjustment coefficient to adjust the voltage and current output by the high-voltage breakdown module. By analyzing the stable characteristics of the electrical data in the historical destruction process, the present invention sets an adjustment coefficient to ensure the synchronous stability of the voltage and current, and then outputs a stable and effective breakdown voltage for data destruction.

[0061] It should be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0062] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the differences between each embodiment and other embodiments are emphasized.

Claims

1. A mobile data destruction system, characterized in that: The system comprises: A high-voltage breakdown module is used to execute a data destruction command and perform a high-voltage breakdown on a data storage medium; A breakdown control module, comprising a data storage unit, a data processing unit and a control unit; A data storage unit is used to store the electrical data sequence in each historical destruction process, the electrical data including two dimensions of voltage and current; all the electrical data sequences of each dimension are arranged to form an electrical data matrix of the corresponding dimension; A data processing unit is used to obtain the disorder influence characteristic value of each electrical data sequence according to the data volatility of the electrical data sequence itself and the difference between the electrical data sequences of different historical destruction processes; fuse the disorder influence characteristic value and the electrical data matrix to obtain the characteristic sequence; obtain the deviation sequence of the electrical data matrix according to the data difference between the electrical data sequence and the standard breakdown electrical data, fuse the deviation sequence and the characteristic sequence to obtain the interference characteristic value sequence under two electrical data dimensions; The control unit is used to obtain an adjustment coefficient according to the correlation of the interference characteristic value sequence under two electrical data dimensions, and adjust the voltage and current output by the high-voltage breakdown module based on the adjustment coefficient.

2. A mobile data destruction system according to claim 1, characterized in that: The data volatility is the coefficient of variation of the electrical data sequence.

3. A mobile data destruction system according to claim 1, characterized in that: The difference between the electrical data sequences between the different historical destruction processes is the DTW distance between the electrical data sequences.

4. A mobile data destruction system according to claim 1, characterized in that: The obtaining of the disorder impact characteristic value of each electrical data sequence comprises: For each historical destruction process, the average difference of the electrical data sequence between the historical destruction process and all other historical destruction processes is taken as the overall difference; the product of the overall difference and the data volatility is normalized to obtain the disorder influence characteristic value of the corresponding electrical data sequence.

5. A mobile data destruction system according to claim 1, characterized in that: The method for acquiring the feature sequence includes: The electrical data sequence is taken as a column in the electrical data matrix; the disorder influence eigenvalues ​​corresponding to each historical destruction process constitute a disorder influence eigenvalue sequence, and the transposed matrix of the disorder influence eigenvalue sequence is multiplied with the electrical data matrix by the matrix multiplication method to obtain the characteristic sequence.

6. A mobile data destruction system according to claim 1, characterized in that: The method for obtaining the deviation sequence includes: The data difference between each element in the electrical data matrix and the standard breakdown electrical data is obtained to construct a deviation matrix; in the deviation matrix, the data differences at the same time of different historical destruction processes are averaged to obtain the average data difference at each time to form the deviation sequence.

7. A mobile data destruction system according to claim 1, characterized in that: The method for obtaining the interference characteristic value sequence includes: The sum of the deviation sequence and the characteristic sequence is used as the interference characteristic value sequence.

8. A mobile data destruction system according to claim 1, characterized in that: The correlation is the absolute value of the Pearson correlation coefficient between the interference feature value sequences in the two electrical data dimensions.

9. A mobile data destruction system according to claim 1, characterized in that: The method for obtaining the adjustment coefficient includes: The correlation is negatively mapped and normalized to obtain an interference weight; a proportional parameter is obtained using the attenuation curve method in the PI control method, the product of the proportional parameter and the interference weight is used as a parameter adjustment amount, and the sum of the proportional parameter and the parameter adjustment amount is used as the adjustment coefficient.

10. A mobile data destruction system according to claim 1, characterized in that: Each time a destruction process is executed, the data storage unit needs to update the historical destruction process data, and the number of historical destruction processes stored in the data storage unit remains unchanged.

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