A mobile data destruction system

Abstract

The present invention relates to the field of electrical data processing technology, and in particular to a mobile data destruction system. The system is provided with a breakdown control module for controlling the voltage and current output by a high-voltage breakdown module. The electrical data in the historical destruction process is analyzed, and by constructing an electrical data matrix, it is convenient to effectively analyze the electrical data fluctuations in the historical destruction process, as well as the data fluctuations at the same time between different historical destruction processes. The response characteristic correlation under the two dimensions of voltage and current is further analyzed, and an adjustment coefficient is obtained to adjust the voltage and current output by the high-voltage breakdown module. The present invention analyzes the stability characteristics of the electrical data in the historical destruction process, sets an adjustment coefficient, ensures the synchronous stability of the voltage and current, and then outputs a stable and effective breakdown voltage 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, data security has become increasingly important. Mobile data destruction, a key means of ensuring data security, has garnered widespread attention. Its core approach involves using a portable device to physically destroy storage media, completely eliminating its storage capacity. This ensures the permanent loss of stored data and effectively prevents data leakage. Currently, high-voltage breakdown is a common method of mobile data destruction. This method utilizes high voltage to destroy storage cells, irreversibly damaging them and rendering the corresponding motherboard unusable. This method cleverly exploits the irreversible damage caused by high-voltage breakdown to motherboard storage cells, achieving complete data destruction. However, to ensure complete data destruction, a stable breakdown voltage is crucial. Only by maintaining a stable breakdown voltage can the integrity of the data destruction process 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 drives, USB flash drives, mobile phones, and tablets, which have significant differences in interface specifications, circuit design, storage principles, and other aspects. On the other hand, the operating 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. Existing mobile data destruction methods mostly rely on high-voltage generators and corresponding switching devices. However, a common flaw of these methods is that in actual operation, potential interference caused by factors such as device type, contact method, and environment is often ignored. When faced with the task of destroying large numbers of devices, unstable breakdown voltages frequently occur. Once the breakdown voltage is unstable, the data of some devices to be destroyed cannot be completely destroyed, leaving a serious risk of data leakage. 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. 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 the data storage medium;

[0007] A breakdown control module, comprising a data storage unit, a data processing unit and a control unit;

[0008] A data storage unit is used to store the electrical data sequence of 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;

[0009] A data processing unit is configured to obtain a disorder influence characteristic value of each electrical data sequence based on the data volatility of the electrical data sequence itself and the difference between the electrical data sequences in different historical destruction processes; fuse the disorder influence characteristic value with the electrical data matrix to obtain a characteristic sequence; obtain a deviation sequence of the electrical data matrix based on the data difference between the electrical data sequence and the standard breakdown electrical data; fuse the deviation sequence with the characteristic sequence to obtain an interference characteristic value sequence in two electrical data dimensions;

[0010] 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.

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

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

[0013] Furthermore, obtaining the disorder impact characteristic value of each electrical data sequence includes:

[0014] 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 impact characteristic value of the corresponding electrical data sequence.

[0015] Furthermore, the method for obtaining the characteristic sequence includes:

[0016] The electrical data sequence is taken as a column in the electrical data matrix; the disorder influence eigenvalue corresponding to each historical destruction process constitutes 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 said characteristic sequence.

[0017] Furthermore, the method for obtaining the deviation sequence includes:

[0018] 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 moment of different historical destruction processes are averaged to obtain the average data difference at each moment to form the deviation sequence.

[0019] Furthermore, the method for obtaining the interference characteristic value sequence includes:

[0020] The sum of the deviation sequence and the characteristic sequence is used as the interference characteristic value sequence.

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

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

[0023] 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 the parameter adjustment amount, and the sum of the proportional parameter and the parameter adjustment amount is used as the adjustment coefficient.

[0024] Furthermore, 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 in a mobile data destruction system, the present invention sets a breakdown control module for controlling the voltage and current output by the high-voltage breakdown module. The present invention analyzes the electrical data in the historical destruction process, and by constructing an electrical data matrix, facilitates effective analysis of the electrical data fluctuations in the historical destruction process, as well as the data fluctuations at the same time between different historical destruction processes, and determines the final interference characteristic value sequence through two-dimensional analysis. Each element in the interference characteristic value sequence represents the actual response result of the interference generated by the environment in the corresponding dimension under the actual destruction process based on the existing feedback control parameters. The response characteristic correlation under the two dimensions of voltage and current is further analyzed. If the characteristics of the two have a significant correlation, it means that the control parameters in the destruction system are appropriate and no excessive adjustment is required. Therefore, an adjustment coefficient can be obtained to adjust the voltage and current output by the high-voltage breakdown module to ensure the synchronous stability of the voltage and current, thereby outputting a stable and effective breakdown voltage for data destruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

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

[0029] Figure 2 A schematic diagram of a mobile data destruction device module provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0030] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a mobile data destruction system according to the present invention. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

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

[0032] See also Figure 2, which shows a schematic diagram of a module of a mobile data destruction device 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 power indicator light and a charging interface. The battery pack consists of multiple rechargeable battery cells. When the system needs power, the battery pack outputs the stored energy in the form of a stable low voltage to the high-voltage transformer and control chip. The high-voltage transformer operates according to the law of electromagnetic induction. When the system is started, the low voltage from the battery pack is connected to the primary winding of the high-voltage transformer. The control chip issues a command to ensure a stable current flows through the primary winding. Under the action of the iron core, the secondary winding induces a high voltage of 30kV and a low current of 0.1mA, executing the high-voltage breakdown operation of the device to be destroyed. The power indicator consists of multiple light-emitting diodes to display the remaining power of the battery pack. The charging port is used to connect to an external charging device to replenish the power of the battery pack. The power switch is the control component for turning the system power on and off, which can start and stop the system. The high-voltage switch powers the high-voltage output according to the signal sent by the control chip. The control chip integrates a microprocessor, sensors, storage unit and various control power supplies. The sensors collect status information of various system components, including but not limited to the battery pack power and the output parameters of the high-voltage transformer, to achieve precise control and complete data destruction. The embodiment of the present invention proposes a mobile data destruction system, which is an improvement on some modules based on the device. The specific scheme of a mobile data destruction system provided by the present invention is described in detail below with reference to the accompanying drawings.

[0033] See also Figure 1 , which shows a block diagram of a mobile data destruction system according to one embodiment of the present invention. The system primarily comprises a high-voltage breakdown module 101 and a breakdown control module 102. The breakdown control module can provide feedback control commands to the high-voltage breakdown module. The breakdown control module 102 also includes a data storage unit 201, a data processing unit 202, and a control unit 203.

[0034] Data storage unit 201 is used to store the electrical data sequence from each historical destruction process. Each data destruction process generates a series of time-series voltage and current data. These two dimensions of data constitute two electrical data sequences. To analyze the impact of data fluctuations during the destruction process, this embodiment of the present invention analyzes the electrical data sequences from multiple historical destruction processes together and arranges them to form electrical data matrices of corresponding dimensions, namely, a voltage dimension electrical data matrix and a current dimension electrical data matrix.

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

[0036] It should be noted that after obtaining the electrical data sequence, the influence of noise information in the data can be reduced by filtering and noise reduction methods. In the embodiment 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] During actual data destruction operations, it can be found that after repeated destruction operations, due to hardware issues with the destruction equipment, the subsequent destruction of data storage media may not be completely complete. Because the destruction process may be affected by various complex interference factors, the output parameters of the high-voltage transformer may fluctuate after a period of destruction, resulting in the inability to maintain a stable high voltage during the high-voltage breakdown process. Therefore, it is necessary to analyze the volatility of historical data to determine the impact of the changing characteristics of historical data on the control parameters of the subsequent destruction process, and then perform feedback adjustments. Therefore, the data processing unit 202 is primarily used to analyze the fluctuations in the horizontal and vertical data in the electrical data matrix, and then determine the feedback impact of the subsequent destruction process.

[0038] Data processing unit 202 first analyzes the data volatility of the electrical data sequence itself. The greater the data volatility, the more unstable the destruction process. It further determines 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 unstable output was generated during the successive historical destruction processes. Combining these two characteristics, the disorder effect characteristic value of each electrical data sequence can be obtained. That is, the disorder effect characteristic value represents the degree of system disorder during a destruction process. The larger the disorder effect characteristic value, the greater the degree of interference influence during the destruction process.

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

[0040] Furthermore, considering that the electrical data during the destruction process should be stable and rated standard electrical data, the greater the data difference between the data sequence and the standard breakdown electrical data, the more unstable the destruction process. Therefore, based on the data difference between the data sequence and the standard breakdown electrical data, a 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. This can then be fused with the feature sequence to obtain an interference eigenvalue sequence under two electrical data dimensions. The interference eigenvalue sequence integrates the original electrical data information, fluctuation information, and deviation information, and can represent the corresponding data characteristics of the actual destruction process under the control parameters of all historical destruction processes.

[0041] For the data destruction process, the stability of electrical data represents stability in two dimensions: voltage data and current data. Therefore, the correlation between the voltage and current variation characteristics should be further analyzed. If a clear lack of correlation occurs, it indicates that the control parameters set using feedback control during the actual control process are no longer able to respond in a timely and effective manner, and additional adjustments to the electrical data are required to ensure the stability of the breakdown voltage and breakdown current. Therefore, the control unit 203 obtains an adjustment coefficient based on the correlation of the interference characteristic value sequence in the 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 an embodiment of the present invention, the data storage unit also has a data update function. Each time a destruction process is executed, the data storage unit needs to update the historical destruction process data. The number of historical destruction processes stored in the data storage unit remains unchanged. In an embodiment of the present invention, based on the storage capacity of the data storage unit, a total of 50 historical destruction process data is stored. Each time a new destruction process is executed, the oldest destruction process of the 50 is removed and the latest destruction process data is added.

[0043] Preferably, in an embodiment of the present invention, the data processing unit obtains the data volatility of the electrical data sequence itself by using the coefficient of variation of the electrical data sequence as the data volatility. A larger coefficient of variation indicates greater fluctuations in the elements of the sequence and more unstable data. Methods for obtaining the coefficient of variation are well known to those skilled in the art and will not be elaborated upon here.

[0044] Preferably, in this embodiment of the present invention, because the electrical data sequences of different historical destruction processes are all time series, a 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 each historical destruction process, it is necessary to calculate the electrical data sequence difference between the historical destruction process and each other historical destruction process.

[0045] Preferably, in an embodiment of the present invention, the method for obtaining the disorder impact characteristic value includes:

[0046] For each historical destruction process, the average difference in the electrical data sequence between that 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 corresponding electrical data sequence's disorder effect characteristic value. Specifically, this embodiment of the present invention uses the product to establish a positive correlation between the overall difference and the data volatility. The greater the overall difference and the greater the data volatility, the more unstable the electrical data in that historical destruction process, and the greater the disorder effect characteristic value.

[0047] It should be noted that the normalization processing in the embodiment of the present invention adopts the softmax function mapping method. In other embodiments, other function mapping or range normalization methods may also be used for implementation, which will not be described in detail here.

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

[0049] Because the electrical data sequence in this embodiment of the present invention is a column in the electrical data matrix, the disorder-affected eigenvalues corresponding to each historical destruction process constitute a disorder-affected eigenvalue sequence. Using matrix multiplication, the transposed matrix of the disorder-affected eigenvalue sequence is multiplied by the electrical data matrix to obtain the eigenvalue sequence. Basic linear algebra operations can effectively integrate the disorder-affected eigenvalues with the electrical data matrix.

[0050] Preferably, in an embodiment 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 to construct a deviation matrix. It should be noted that the data difference in the embodiment of the present invention is the absolute value of the difference.

[0052] In the deviation matrix, the data differences at the same moment in different historical destruction processes are averaged to obtain the average data difference at each moment, forming the deviation sequence.

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

[0054] Preferably, in an embodiment of the present invention, the method for obtaining the interference characteristic value sequence includes:

[0055] Because the lengths of the deviation sequence and the characteristic sequence are the same, which are both the time series lengths of the electrical data sequence, the sum of the deviation sequence and the characteristic sequence can be directly used as the interference characteristic value sequence.

[0056] Preferably, in the embodiment of the present invention, the correlation is the absolute value of the Pearson correlation coefficient between the interference feature value sequences in the two electrical data dimensions. The larger the absolute value of the Pearson correlation coefficient, the more linearly correlated the interference feature value sequences in the two dimensions are, that is, the more similar the variation characteristics are.

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

[0058] The correlation is negatively mapped and normalized to obtain the interference weight. The stronger the correlation, the stronger the stability of the synchronization of voltage and current under actual feedback control, which means that the difference in response to interference under the current control parameters is smaller, and the adjustment range of the corresponding proportional parameter is smaller; if the correlation of the synchronous and stable changes of voltage and current under the influence of interference in the actual response control process is weaker, it means that the difference in response to interference under the current control parameters is larger, and the adjustment range of the corresponding proportional parameter is larger. Therefore, it is necessary to negatively map the correlation and normalize it to obtain an interference weight with a value range between 0 and 1. It should be noted that in one embodiment of the present invention, because the correlation is the absolute value of the Pearson coefficient, its value range is already between 0 and 1, so the interference weight can be obtained by directly subtracting the positive integer 1 from the correlation.

[0059] The proportional parameter is obtained using the attenuation curve method in the PI control method. That is, the proportional parameter is an initial parameter, and the interference weight 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 embodiment of the present invention sets a breakdown control module for controlling the voltage and current output by the high-voltage breakdown module. The electrical data in the historical destruction process is analyzed, and by constructing an electrical data matrix, it is convenient to effectively analyze the electrical data fluctuations in the historical destruction process and the data fluctuations at the same time between different historical destruction processes. The response characteristic correlation under the two dimensions of voltage and current is further analyzed, and the adjustment coefficient is obtained to adjust the voltage and current output by the high-voltage breakdown module. The present invention analyzes the stability characteristics of the electrical data in the historical destruction process, sets the adjustment coefficient, ensures 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 order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0062] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

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 the 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 of 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 configured to obtain a disorder influence characteristic value of each electrical data sequence based on the data volatility of the electrical data sequence itself and the difference between the electrical data sequences in different historical destruction processes; fuse the disorder influence characteristic value with the electrical data matrix to obtain a characteristic sequence; obtain a deviation sequence of the electrical data matrix based on the data difference between the electrical data sequence and the standard breakdown electrical data; fuse the deviation sequence with the characteristic sequence to obtain an interference characteristic value sequence in two electrical data dimensions; A control unit is configured to obtain an adjustment coefficient based on 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; wherein, the stronger the correlation, the stronger the stability of the synchronization of the voltage and current; 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 the parameter adjustment amount, and the sum of the proportional parameter and the parameter adjustment amount is used as 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 includes: 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 impact characteristic value of the corresponding electrical data sequence.

5. A mobile data destruction system according to claim 1, characterized in that: The method for obtaining the feature sequence includes: The electrical data sequence is taken as a column in the electrical data matrix; the disorder influence eigenvalue corresponding to each historical destruction process constitutes 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 said 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 moment of different historical destruction processes are averaged to obtain the average data difference at each moment 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. The 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. The mobile data destruction system according to claim 1, characterized in that: The data storage unit needs to update the historical destruction process data each time a destruction process is executed, and the number of historical destruction processes stored in the data storage unit remains unchanged.

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