CN117349632A - Analysis method and device for magnetic stripe card time sequence and card swiping machine - Google Patents
Analysis method and device for magnetic stripe card time sequence and card swiping machine Download PDFInfo
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Abstract
The application relates to the technical field of magnetic stripe card decoding, and discloses an analysis method for a magnetic stripe card time sequence, which comprises the following steps: performing periodic analysis processing on a time sequence generated by swiping the magnetic stripe card to generate a periodic sequence; performing cycle prediction on the cycle sequence to obtain a target cycle predicted value; and according to the target period predicted value, carrying out data bit judgment on the time sequence to obtain the data bit of the magnetic stripe card magnetic track. The method can improve the accuracy of magnetic stripe card magnetic track data bit judgment. The application also discloses an analysis device for the magnetic stripe card time sequence and a card swiping machine.
Description
Technical Field
The present invention relates to the field of magnetic stripe card decoding technologies, and for example, to a method and an apparatus for analyzing a magnetic stripe card time sequence, and a card swiping machine.
Background
Currently, magnetic cards are card-shaped magnetic recording media that record characters and digital information using a magnetic carrier for identification or other purposes. Magnetic cards are typically made of high strength, high temperature resistant plastic or paper coated plastic, which provides moisture protection, wear resistance, and flexibility. Such as a bank card. Magnetic stripe cards are one of the common magnetic cards. The magnetic stripe card is composed of a plastic card and a magnetic stripe attached to the plastic card, and three magnetic tracks for storing information are arranged on the magnetic stripe. When the magnetic stripe card performs a card swiping operation, the magnetic stripe card cuts the coil by the external magnetic force of the magnetic stripe card through the working magnetic head provided with the coil, so that induced electromotive force is generated in the coil, and signal transmission is realized. Because the magnetic stripe card swiping speeds are different, a larger phase difference can be generated in the period between the front end of swiping and the rear end of swiping. Meanwhile, the magnetic poles on the surface of the magnetic stripe card are worn, so that the signal detection result fluctuates. In addition, external interference can also interfere with signal detection during card swiping, and the accuracy of data bit judgment of magnetic stripe card magnetic tracks is affected.
In order to ensure accurate judgment of data bits of a magnetic stripe card, a related art discloses a time-series data bit judgment method, which comprises the following steps: selecting the period values of different data bits of the time sequence; averaging the period values of different data bits to obtain an average period value; the average period value is taken as a period reference value of the data bit.
In the process of implementing the embodiments of the present disclosure, it is found that at least the following problems exist in the related art:
the average period value obtained by averaging in the related art has an error with the actual period value, and the period reference value of the data bit can influence the judgment result of the time sequence data bit, so that the accuracy of judging the magnetic stripe card track data bit is reduced.
It should be noted that the information disclosed in the foregoing background section is only for enhancing understanding of the background of the present application and thus may include information that does not form the prior art that is already known to those of ordinary skill in the art.
Disclosure of Invention
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview, and is intended to neither identify key/critical elements nor delineate the scope of such embodiments, but is intended as a prelude to the more detailed description that follows.
The embodiment of the disclosure provides an analysis method, an analysis device and a card swiping machine for a magnetic stripe card time sequence, so as to improve the accuracy of magnetic track data bit judgment when a magnetic stripe card is processed.
In some embodiments, the method comprises: performing periodic analysis processing on a time sequence generated by swiping the magnetic stripe card to generate a periodic sequence; performing cycle prediction on the cycle sequence to obtain a target cycle predicted value; and according to the target period predicted value, carrying out data bit judgment on the time sequence to obtain the data bit of the magnetic stripe card magnetic track.
In some embodiments, the periodic analysis processing is performed on the time sequence generated by swiping the magnetic stripe card to generate a periodic sequence, including: extracting data bits in the time sequence and clock period values corresponding to the data bits; under the condition that the data bit is bit 0, selecting a clock period value corresponding to the data bit as a target period value; under the condition that the data bit is bit 1, selecting the sum of the clock period value corresponding to the data bit and the adjacent clock period value as a target period value; and constructing a periodic sequence according to the respective target periodic values of different periodic numbers.
In some embodiments, performing cycle prediction on a cycle sequence to obtain a target cycle prediction value includes: determining a historical period predicted value associated with the period sequence; long-term prediction is carried out on the historical period predicted value, and a first period predicted value is obtained; short-term prediction is carried out on the historical period predicted value, and a second period predicted value is obtained; and carrying out weight calculation on the first cycle predicted value and the second cycle predicted value to obtain a target cycle predicted value.
In some embodiments, long-term predicting the historical periodic prediction value to obtain the first periodic prediction value includes: selecting a history period predicted value of a long period to perform straight line fitting or polynomial fitting to obtain a fitting straight line of the period number and the period predicted value; determining a first cycle predicted value based on the fitted line according to the current cycle number; and/or performing short-term prediction on the historical period predicted value to obtain a second period predicted value; selecting a history period predicted value of a short period to perform curve fitting, and obtaining a fitting curve of the period number and the period predicted value; and determining a second cycle predicted value based on the fitted curve according to the current cycle number.
In some embodiments, the pair ofThe first cycle predicted value and the second cycle predicted value are weighted to obtain a target cycle predicted value, and the target cycle predicted value is calculated according to the following formula:，the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>For the target period prediction value, +.>Representing a first cycle predicted value, a second cycle predicted value and an actual cycle value, respectively, +.>Indicating error, & lt>The first weight value, the second weight value, the third weight value, and the fourth weight value are represented, respectively.
In some embodiments, weighting the first period prediction value and the second period prediction value to obtain a target period prediction value includes calculating the target period prediction value according to the following formula: ，The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>For the target period prediction value, +.>Representing a first cycle predicted value, a second cycle predicted value and an actual cycle value, respectively, +.>Respectively represent a first weight value and a second weight valueAnd a third weight value.
In some embodiments, the first weight value is determined as follows: determining a first weight value according to the interference degree of the time sequence; and/or determining the second weight value as follows: and determining a second weight value according to the card swiping speed of the magnetic stripe card.
In some embodiments, making a data bit decision for the time series based on the target period prediction value to obtain data bits for the magnetic stripe card track comprises: determining a first judgment threshold of bit 0 according to the target period predicted value; determining a second judgment threshold of the bit 1 according to the target period predicted value; and carrying out data bit judgment on the time sequence according to the first judgment threshold and the second judgment threshold to obtain the data bit of the magnetic stripe card track.
In some embodiments, making a data bit decision for the time series based on the target period prediction value to obtain data bits for the magnetic stripe card track comprises: determining a third judgment threshold of the interference signal according to the target period predicted value; under the condition that a suspected interference signal exists in the time sequence, acquiring a current time stamp of the suspected interference signal; and under the condition that the current time stamp is smaller than a third judgment threshold, determining the suspected interference signal as the interference signal.
In some embodiments, the apparatus includes a processor and a memory storing program instructions, the processor being configured, when executing the program instructions, to perform an analysis method for a magnetic stripe card time series as described above.
In some embodiments, the card reader comprises: a card swiping machine body; the analysis device for the magnetic stripe card time sequence is arranged on the card swiping machine body.
The analysis method and device for the magnetic stripe card time sequence and the magnetic stripe card provided by the embodiment of the disclosure can realize the following technical effects:
according to the method, the device and the system, the time sequence is subjected to periodic analysis processing to generate a periodic sequence, and then the periodic sequence is subjected to periodic prediction to obtain a target periodic predicted value. By carrying out period prediction on the period sequence, the change trend of the period value of the period sequence can be reflected through the target period predicted value, and the accuracy of the obtained target period predicted value can be improved. Finally, according to the target period predicted value, the data bits of the time sequence are judged to obtain the data bits of the magnetic stripe card magnetic track. The embodiment of the disclosure executes the data bit judgment of the magnetic stripe card magnetic track data based on the target cycle predicted value of the cycle sequence generated by the cycle analysis processing, which is beneficial to improving the accuracy of the magnetic stripe card magnetic track data bit judgment.
The foregoing general description and the following description are exemplary and explanatory only and are not restrictive of the application.
Drawings
One or more embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements, and in which like reference numerals refer to similar elements, and in which:
FIG. 1-1 is a schematic diagram of a card swiping structure of a conventional card swiping machine;
FIGS. 1-2 are schematic diagrams of sequentially generated analog waveforms, binary sequences, time sequences, and periodic sequences when a magnetic stripe card is swiped, provided by embodiments of the present disclosure;
FIG. 2 is a schematic diagram of an analysis method for magnetic stripe card time series provided by an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of an analysis method for a magnetic stripe card time series provided by an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of another method of analysis for a magnetic stripe card time series provided by an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of another method of analysis for a magnetic stripe card time series provided by an embodiment of the present disclosure;
FIG. 6 is a schematic diagram of another method of analysis for a magnetic stripe card time series provided by an embodiment of the present disclosure;
FIG. 7 is a schematic diagram of another method of analysis for a magnetic stripe card time series provided by an embodiment of the present disclosure;
FIG. 8-1 is a schematic diagram of a time sequence of an embodiment of the present disclosure;
FIG. 8-2 is a schematic illustration of a periodic sequence generated via periodic analysis based on the time series of FIG. 8-1, in accordance with an embodiment of the present disclosure;
FIG. 9 is a schematic illustration of an application of an embodiment of the present disclosure;
FIG. 10 is a schematic diagram of an analysis device for a magnetic stripe card time series provided by an embodiment of the present disclosure.
Detailed Description
So that the manner in which the features and techniques of the disclosed embodiments can be understood in more detail, a more particular description of the embodiments of the disclosure, briefly summarized below, may be had by reference to the appended drawings, which are not intended to be limiting of the embodiments of the disclosure. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may still be practiced without these details. In other instances, well-known structures and devices may be shown simplified in order to simplify the drawing.
The terms first, second and the like in the description and in the claims of the embodiments of the disclosure and in the above-described figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate in order to describe embodiments of the present disclosure. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion.
The term "plurality" means two or more, unless otherwise indicated.
In the embodiment of the present disclosure, the character "/" indicates that the front and rear objects are an or relationship. For example, A/B represents: a or B.
The term "and/or" is an associative relationship that describes an object, meaning that there may be three relationships. For example, a and/or B, represent: a or B, or, A and B.
The term "corresponding" may refer to an association or binding relationship, and the correspondence between a and B refers to an association or binding relationship between a and B.
Fig. 1-1 is a schematic diagram of a card swiping structure of a conventional card swiping machine. 1-2 are schematic diagrams of analog waveforms, binary sequences, time sequences, and periodic sequences that are sequentially generated when a magnetic stripe card is swiped, provided by embodiments of the present disclosure.
As shown in connection with fig. 1-1, the card reader includes a card swiping structure. The card swiping structure comprises a magnetic head and a plurality of signal processing circuits. Each signal processing circuit comprises an operational amplifier, an analog-to-digital converter and a signal detection circuit. 1-2, when the magnetic stripe card performs a card swiping operation, magnetic lines of force corresponding to each track of the magnetic stripe card cut a magnetic head coil, the magnetic head outputs an analog waveform through an operational amplifier when magnetic poles are converted, the analog waveform outputs a binary sequence through an analog-to-digital converter, and the binary sequence outputs a time sequence through a signal detection circuit. The signal detection circuit is used for recording the time interval between the adjacent peaks of the analog waveform, storing the time interval as a clock period and forming a time sequence. I.e. the time series indicates that the respective clock cycles are recorded at different times and that a time count value corresponds to a clock cycle of a complete track data bit.
Typically, the magnetic stripe card begins with a series of bits 0 per track to provide a clock period that determines the data bits of the track. The data bit at the corresponding position of the magnetic track can be determined to be 1 bit 0 or 1 bit by whether jump exists in one clock period, but the clock period is changed along with the change of the card swiping speed of the magnetic stripe card, namely the front end period and the back end period of the card swiping of the magnetic stripe card can generate phase difference. Meanwhile, because the distribution of magnetic poles on the surface of the card swiping machine fluctuates and the detection of the signal processing circuit also fluctuates, and meanwhile, the external interference pulse also has the possibility of being misjudged as a magnetic pole converted signal, the judgment of magnetic track data bits can be influenced by the factors, so that misjudgment of the data bit judgment of a time sequence is caused, and the accuracy of the magnetic track data bit judgment of the magnetic stripe card is influenced.
Based on the above card swiping structure, referring to fig. 1-2 and fig. 3, an embodiment of the disclosure provides an analysis method for a magnetic stripe card time sequence, including:
s01, the card swiping machine performs periodic analysis processing on the time sequence generated by the magnetic stripe card swiping to generate a periodic sequence.
S02, the card swiping machine predicts the period of the period sequence to obtain a target period predicted value.
S03, the card swiping machine judges the data bit of the time sequence according to the target period predicted value to obtain the data bit of the magnetic stripe card track.
By adopting the analysis method for the magnetic stripe card time sequence provided by the embodiment of the disclosure, the embodiment of the disclosure performs periodic analysis processing on the time sequence to generate a periodic sequence, and then performs periodic prediction on the periodic sequence to obtain a target periodic predicted value. By carrying out period prediction on the period sequence, the change trend of the period value of the period sequence can be reflected through the target period predicted value, and the accuracy of the obtained target period predicted value can be improved. Finally, according to the target period predicted value, the data bits of the time sequence are judged to obtain the data bits of the magnetic stripe card magnetic track. The embodiment of the disclosure executes the data bit judgment of the magnetic stripe card magnetic track data based on the target cycle predicted value of the cycle sequence generated by the cycle analysis processing, which is beneficial to improving the accuracy of the magnetic stripe card magnetic track data bit judgment.
In an embodiment of the present disclosure, the time series of FIGS. 1-2 is based on the analysis method described above for the time series of magnetic stripe cards to generate the periodic sequence of FIGS. 1-2.
Optionally, referring to fig. 4, the card swiping machine performs a periodic analysis process on a time sequence generated by swiping a magnetic stripe card to generate a periodic sequence, including:
S11, the card swiping machine extracts data bits in the time sequence and clock period values corresponding to the data bits.
S12, when the data bit is bit 0, the card swiping machine selects the clock period value corresponding to the data bit as a target period value.
S13, under the condition that the data bit is bit 1, the card swiping machine selects the sum of the clock period value corresponding to the data bit and the adjacent clock period value as a target period value.
S14, the card swiping machine constructs a period sequence according to respective target period values of different periods.
Thus, embodiments of the present disclosure first extract the data bits in the time series and the clock period value corresponding to each data bit. Thereafter, since bit 0 is composed of one clock cycle in the time sequence and bit 1 is composed of two clock cycles in the time sequence, the disclosed embodiment selects the clock cycle value corresponding to the data bit as the target cycle value of the data bit when the data bit is bit 0, and takes the sum of the time value corresponding to the data bit and the adjacent clock cycle value as the target cycle value when the data bit is bit 1. Finally, the embodiment of the disclosure constructs a generating period sequence according to the respective target period values of different periods. In this way, according to the embodiment of the disclosure, the cycle sequence with the cycle number as the transverse dimension and the target cycle values with different cycle numbers as the longitudinal dimension can be constructed according to the corresponding relation between the data bit 0 and the data bit 1 and the time sequence, so as to provide accurate cycle value data for the subsequent cycle prediction.
In practical applications, fig. 8-1 shows a time series, the horizontal axis shows time counts, and the vertical axis shows time intervals for different time counts. Fig. 8-2 shows a period sequence generated based on the construction of the time sequence of fig. 8-1, with the horizontal axis representing the period count and the vertical axis representing the target period value for each of the different period counts.
As shown in fig. 8-1 and 8-2, in fig. 8-1, the respective clock cycles of the 1 to 20 time count values are 40, 39, 40, 19, 20, 39, 20, 19, 39, 38, 20, 19, 38, 39, 37, 38, 19, 20 in order.
Taking the time count value 1 as an example, the clock period corresponding to the time count value 1 and the data bit corresponding to the time count value 1 are bit 0, the clock period value corresponding to the data bit is selected as the target period value, that is, the period value corresponding to the period count value 1 is set as 40.
Taking the time count value 2 as an example, the clock period corresponding to the time count value 2 and the data bit corresponding to the time count value 4 are bit 0, the clock period value corresponding to the data bit is selected as the target period value, that is, the period value corresponding to the period count value 2 is set as 40.
Taking the time count value 3 as an example, the clock period corresponding to the time count value 3 and the data bit corresponding to the time count value 3 are bit 0, the clock period value corresponding to the data bit is selected as the target period value, that is, the period value corresponding to the period count value 3 is set to 39.
Taking the time count value 4 as an example, the clock period corresponding to the time count value 4 and the data bit corresponding to the time count value 4 are bit 0, the clock period value corresponding to the data bit is selected as the target period value, that is, the period value corresponding to the period count value 4 is set to 40.
Taking the time count value 5 as an example, the clock period corresponding to the time count value 5 and the data bit corresponding to the time count value 5 are bit 1, the sum 39 of the clock period 19 corresponding to the data bit and the adjacent clock period value 20 is selected as the target period value, i.e. the period value corresponding to the period count value 5 is set to 39.
In the above manner, according to the respective clock cycle values of the time count values of 1 to 20, the target cycle values of 1 to 16 cycles can be determined to be 40, 39 40, 39, 38, 39, 37, 38, 39. I.e. to construct the periodic sequence shown in fig. 8-2.
The calculation of the target cycle value of the cycle numbers other than 1 to 16 in fig. 8-2 according to the embodiments of the present disclosure will not be repeated.
Optionally, referring to fig. 2 and fig. 5, the card reader performs cycle prediction on the cycle sequence to obtain a target cycle prediction value, including:
s21, determining a historical period predicted value associated with the period sequence by the card swiping machine.
S22, the card swiping machine predicts the historical period predicted value for a long time to obtain a first period predicted value.
S23, the card swiping machine carries out short-term prediction on the historical period predicted value to obtain a second period predicted value.
And S24, the card swiping machine performs weight calculation on the first cycle predicted value and the second cycle predicted value to obtain a target cycle predicted value.
Thus, the long-term prediction of the predicted value of the periodic sequence can obtain the long-term change rule of the periodic value of the periodic sequence, thereby reflecting the change of the card swiping speed of the magnetic stripe card. Accordingly, embodiments of the present disclosure determine a historical period predictor associated with a periodic sequence, and then long-term predict the historical period predictor to obtain a first period predictor. The predicted value of the periodic sequence is subjected to short-term prediction, so that the short-term change rule of the periodic value of the periodic sequence can be obtained, and the regular jitter condition of magnetic pole distribution fluctuation and the like along with an external interference signal or the surface of a card swiping machine when a magnetic stripe card is swiped is reflected. Finally, the embodiment of the disclosure performs weight calculation on the two predicted period values obtained by prediction to obtain the target predicted period value, so that the calculated target predicted period value gives consideration to the change of the card swiping speed and the regular data jitter, the accurate prediction of the target predicted period value is realized, and compared with the method for predicting the period by using the average value of the predicted period values, the method has higher accuracy, is favorable for realizing the accurate determination of time sequence data bits, and improves the accuracy of magnetic stripe card track data bit determination.
In a specific embodiment, as shown in connection with FIG. 2, the analysis method for magnetic stripe card time series performs time series analysis based on the following principles:
and the card swiping machine performs periodic analysis processing on the time sequence generated by the card swiping of the magnetic stripe card to generate a periodic sequence.
The card swiping machine determines a historical period predicted value associated with the period sequence; then, carrying out long-term prediction on the historical period predicted value to obtain a first period predicted value, and carrying out short-term prediction on the historical period predicted value to obtain a second period predicted value; and then, carrying out weight calculation on the first cycle predicted value and the second cycle predicted value to obtain a target cycle predicted value.
And the card swiping machine judges the data bits of the time sequence according to the target period predicted value to obtain the data bits of the magnetic stripe card track.
Optionally, the card swiping machine performs long-term prediction on the historical period predicted value to obtain a first period predicted value, including: the card swiping machine selects a history period predicted value of a long period to perform straight line fitting or polynomial fitting to obtain a fitting straight line of the period number and the period predicted value; and the card swiping machine determines a first cycle predicted value based on the fitted straight line according to the current cycle number. And/or the number of the groups of groups,
and the card swiping machine carries out short-term prediction on the historical period predicted value to obtain a second period predicted value. Selecting a history period predicted value of a short period to perform curve fitting, and obtaining a fitting curve of the period number and the period predicted value; and the card swiping machine determines a second period predicted value based on the fitted curve according to the current period number.
The long-period historical period predicted value represents a first preset number of continuous period historical period values. The short-period historical period prediction value represents a historical period value of a second preset number of periods continuous. It will be appreciated that the long period historical period prediction value includes at least the period value of the previous period number adjacent to the current period number and the short period historical period prediction value includes at least the period value of the previous period number adjacent to the current period number. The first preset number and the second preset number can be set according to specific requirements. As an example, the first preset number is greater than or equal to 10. The second predetermined number is less than 10.
In this way, the first period predicted value obtained by straight line fitting reflects the change of the card swiping speed, and meanwhile, the second period predicted value obtained by curve fitting reflects the regular data jitter, so that the accurate prediction of the target period predicted value is realized, and the accuracy of magnetic stripe card track data bit judgment is improved.
In one specific example, fig. 9 shows a schematic diagram of a fitted straight line and a fitted curve generated by each of the long-term prediction and the short-term prediction. As shown in fig. 9, the horizontal axis n represents the number of cycles. The vertical axis represents the respective cycle values for the different cycles. In fig. 9, the broken line indicates that the periods are adjacent and the period values corresponding to the adjacent periods are i and i+1, respectively. The fitting straight line corresponding to the long-term prediction can be obtained after the long-term prediction is carried out on the historical period predicted value, and the fitting curve corresponding to the short-term prediction can be obtained after the short-term prediction is carried out on the historical period predicted value.
Optionally, the card swiping machine selects a history period predicted value of a long period to perform straight line fitting or polynomial fitting to obtain a fitting straight line of the period number and the period predicted value; the card reader determines a first cycle predicted value based on a fitted straight line according to the current cycle number, and comprises:
the card swiping machine predicts a value T according to the historical cycle of the cycle number 1 to N 1 To T N Performing straight line fitting to obtain cycle numbers 1-N and a cycle predictive value T 1 To T N Is defined by y=ax+b; wherein a long period represents a period number of 1 to N. Where a represents the slope and b represents the intercept. N can be set according to specific requirements.
The card swiping machine determines that the first cycle predicted value is a (n+1) +b based on the fitting straight line y=ax+b according to the current cycle number n+1.
It should be noted that, regarding the specific manner of the straight line fitting and the polynomial fitting, embodiments of the present disclosure may not be limited in particular.
Optionally, the card reader performs short-term prediction on the historical period predicted value to obtain a second period predicted value. Selecting a history period predicted value of a short period to perform curve fitting, and obtaining a fitting curve of the period number and the period predicted value; the card reader determines a second period predicted value based on the fitted curve according to the current period number, and comprises the following steps:
The card swiping machine predicts a value T according to the historical period of the periods Q to M 1 To T M Performing curve fitting to obtain cycle numbers Q-M and cycle predictive value T Q To T M Is a fitting curve of (a); wherein the short period represents the number of periods Q to M. Q and M may be set according to specific requirements, e.g., Q-M is less than 10. The fitted curve may be a unitary quadratic function or a unitary cubic function. With respect to the specific manner of curve fitting, embodiments of the present disclosure may not be particularly limited thereto.
And the card swiping machine determines a second period predicted value based on the fitting curve according to the current period number M+1.
Optionally, the card reader performs weight calculation on the first period predicted value and the second period predicted value to obtain a target period predicted value, including the card reader calculating the target period predicted value according to the following formula:
，/>。
wherein,for the target period prediction value, +.>Representing a first cycle predicted value, a second cycle predicted value and an actual cycle value, respectively, +.>Indicating error, & lt>The first weight value, the second weight value, the third weight value, and the fourth weight value are represented, respectively.
In this way, based on the first term calculation formula of the target period predicted value, in order to achieve both the change of the card swiping speed and the regular data jitter, and achieve the accurate prediction of the target period predicted value, the embodiment of the disclosure calculates the target period predicted value based on the weight function, and when performing weight calculation, the first period predicted value and the second period predicted value, the actual period value, the error first weight value, the second weight value, the third weight value and the fourth weight value are respectively given. Thus, the error is also included in the calculation of the target period predicted value, and the accurate prediction of the target period predicted value is further improved.
Optionally, the card reader performs weight calculation on the first period predicted value and the second period predicted value to obtain a target period predicted value, including the card reader calculating the target period predicted value according to the following formula:
，/>。
wherein,for the target period prediction value, +.>Representing a first cycle predicted value, a second cycle predicted value and an actual cycle value, respectively, +.>Respectively representing a first weight value, a second weight value and a third weight value.
In this way, based on the second term calculation formula of the target period predicted value, after the magnetic stripe card swipes the card to obtain the time sequence, there is a case that the error is very small or even zero, and at this time, the error is not required to be taken into consideration of the target period predicted value, so that the first, second and third weight values are directly given to the first, second and actual period predicted values.
It should be noted that, when the card swiping machine determines that there is no regular data jitter or the regular data jitter is not obvious according to the time sequence, the second term calculation formula may be selected to predict the target period value, and when the time sequence determines that there is more obvious data jitter, the first term calculation formula is selected to predict the target period value.
Optionally, the card reader determines the first weight value as follows: and the card swiping machine determines a first weight value according to the interfered degree of the time sequence. Wherein the greater the degree of interference, the greater the first weight value.
Optionally, the card reader determines the second weight value as follows: and the card swiping machine determines a second weight value according to the card swiping speed of the magnetic stripe card.
The faster the card swiping speed is, the higher the second weight value is.
In this way, the target period prediction value can be predicted more accurately.
Referring to FIG. 6, another method for analyzing a time series of magnetic stripe cards is provided according to an embodiment of the present disclosure, including:
s31, the card swiping machine performs periodic analysis processing on the time sequence generated by the magnetic stripe card swiping to generate a periodic sequence.
S32, the card swiping machine predicts the period of the period sequence to obtain a target period predicted value.
S33, the card swiping machine determines a first judgment threshold of bit 0 according to the target period predicted value.
S34, the card swiping machine determines a second judgment threshold of the bit 1 according to the target period predicted value.
And S35, the card swiping machine judges the data bits of the time sequence according to the first judgment threshold and the second judgment threshold to obtain the data bits of the magnetic stripe card magnetic track.
By adopting the analysis method for the magnetic stripe card time sequence provided by the embodiment of the disclosure, after the period sequence is subjected to period prediction to obtain the target period predicted value, the first judgment threshold of the bit 0 and the second judgment threshold of the bit 1 can be determined according to the target period predicted value, and then the data bit of the time sequence is judged according to the two judgment thresholds, so that the magnetic stripe card track data bit can be obtained more accurately.
As an example, the card reader determines a first decision threshold of bit 0 according to the target period prediction value, including:
the card swiping machine determines a first lower threshold according to the product of the target period predicted value and the bit 0 lower threshold.
The card swiping machine determines a first upper threshold according to the product of the target period predicted value and the bit 0 upper threshold.
The card swiping machine constructs a first judgment threshold [ a first lower limit threshold value and a first upper limit threshold value ] according to the first lower limit threshold value and the first upper limit threshold value.
Wherein, the lower threshold of the bit 0 can be 90%, and the upper threshold of the bit 0 can be 110%.
As another example, the card reader determining the second decision threshold for bit 1 based on the target period prediction value includes:
the card swiping machine determines a second lower threshold according to the product of the target period predicted value and the bit 1 lower threshold.
The card swiping machine determines a second upper threshold according to the product of the target period predicted value and the bit 1 upper threshold.
And the card swiping machine constructs a first judgment threshold [ a second lower limit threshold value and a second upper limit threshold value ] according to the second lower limit threshold value and the second upper limit threshold value.
Wherein, the lower threshold of bit 1 may be 40% and the upper threshold of bit 1 may be 60%.
Optionally, referring to fig. 7, the card swiping machine performs data bit determination on the time sequence according to the target period predicted value to obtain data bits of the magnetic stripe card track, including:
s41, the card swiping machine determines a third judgment threshold of the interference signal according to the target period predicted value. The third decision threshold represents a third lower threshold.
S42, the card swiping machine obtains the current time stamp of the suspected interference signal under the condition that the suspected interference signal exists in the time sequence.
S43, determining that the suspected interference signal is an interference signal by the card swiping machine under the condition that the current time stamp is smaller than a third judgment threshold.
In this way, the embodiment of the disclosure can judge the suspected interference signal by combining the judging threshold of the data bit 0 and the data bit 1 and the target period predicted value, thereby realizing accurate judgment of the magnetic stripe card track data bit.
In another practical application, referring to fig. 1-2, in the time sequence, a suspected interference signal exists in a clock period corresponding to the time count value k+3.
Firstly, the card swiping machine predicts a value according to a target period. Since the decision condition of the data bit 1 is that there is one magnetic pole transition per clock cycle and the ratio of half cycle of the data bit 1 to the clock cycle is greater than or equal to 40% and less than or equal to 60%. Therefore, the card reader predicts the value +_ according to the target period>A third decision threshold of the interference signal is determined to be +.>。
Then, the card reader acquires the current time stamp S (k+3) of the suspected interference signal. In case S (k+3)<And determining that the current time stamp is smaller than a third judgment threshold, and determining that the suspected interference signal is an interference signal.
Finally, since the data bit 1 is composed of two clock cycles in the time series, the card reader sums S (k+3) and S (k+4) to obtain a sum value, and makes a decision of the data bit on the sum value.
In another practical application, as shown in fig. 8-1 and 8-2, the method for analyzing the time sequence of the magnetic stripe card specifically performs the following steps:
in step S101, the card reader uses a straight line fitting to the period values 0 to 33 according to the time sequence and the period sequence to obtain a formula y= -0.0535 x+ 39.394. Wherein x is the count value of the formula, and y is the period predicted value. From this, a long-term predictive value of the cycle count 34 is calculated, x=34, y=37.57 (i.e., a 0 ). Wherein the period count value 34 corresponds to a time series of count values 45 and 46.
Step S102, the card reader reads the period value of 5 points (namely, the count value is 29 to 33) near the point 34 of the adjacent period, performs quadratic curve fitting and obtains the formula of y=0.0714 x 2 0.3286 x+38. Wherein x is the count value of the formula, and y is the period predicted value. From this, a short-term predictive value of the cycle count 34 is calculated, x=5, y= 37.99 (i.e., a 1 ) 。
Step S103, the card reader obtains the current period as 38 (i.e. A 2 ) Error is 0 (i.e. A 3 ) And input to，/>. Wherein (1)>Respectively 03, 0.5,0.2, 0.0, and based on this, the target cycle predicted value of the cycle count 34 is calculated as 37.87.
In step S104, the error between the target period predicted value and the time series is 0.3%. The target period predicted value of the time series average was 38.44, and the error thereof was 1.1%.
As shown in connection with FIG. 10, an embodiment of the present disclosure provides an analysis device 200 for a magnetic stripe card time series, including a processor 700 and a memory 701. Optionally, the apparatus 70 may further comprise a communication interface (Communication Interface) 702 and a bus 703. The processor 700, the communication interface 702, and the memory 701 may communicate with each other through the bus 703. The communication interface 702 may be used for information transfer. The processor 700 may invoke logic instructions in the memory 701 to perform the analysis method for magnetic stripe card time series of the above-described embodiments.
Further, the logic instructions in the memory 701 may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand alone product.
The memory 701 is used as a computer readable storage medium for storing a software program, a computer executable program, and program instructions/modules corresponding to the methods in the embodiments of the present disclosure. The processor 100 executes the functional applications and data processing by executing the program instructions/modules stored in the memory 701, i.e., implements the analysis method for magnetic stripe card time series in the above-described embodiments.
Memory 701 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created according to the use of the terminal device, etc. In addition, the memory 701 may include a high-speed random access memory, and may also include a nonvolatile memory.
The embodiment of the disclosure provides a card swiping machine, comprising: a card reader body, and the above-described analyzing device 200 for magnetic stripe card time series. The analyzing device 200 for the magnetic stripe card time series is mounted to the card reader body. The mounting relationships described herein are not limited to being placed within the body of the card reader, but include mounting connections to other components of the card reader, including but not limited to physical, electrical, or signaling connections, etc. Those skilled in the art will appreciate that the analysis device 200 for magnetic stripe card time series may be adapted to a viable card swiping machine body to achieve other viable embodiments.
Embodiments of the present disclosure provide a computer readable storage medium storing computer executable instructions configured to perform the above-described analysis method for magnetic stripe card time series.
Embodiments of the present disclosure may be embodied in a software product stored on a storage medium, including one or more instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of a method according to embodiments of the present disclosure. While the aforementioned storage medium may be a non-transitory storage medium, such as: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
The above description and the drawings illustrate embodiments of the disclosure sufficiently to enable those skilled in the art to practice them. Other embodiments may involve structural, logical, electrical, process, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in, or substituted for, those of others. Moreover, the terminology used in the present application is for the purpose of describing embodiments only and is not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a," "an," and "the" (the) are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and/or" as used in this application is meant to encompass any and all possible combinations of one or more of the associated listed. Furthermore, when used in this application, the terms "comprises," "comprising," and/or "includes," and variations thereof, mean that the stated features, integers, steps, operations, elements, and/or components are present, but that the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof is not precluded. Without further limitation, an element defined by the phrase "comprising one …" does not exclude the presence of other like elements in a process, method or apparatus comprising such elements. In this context, each embodiment may be described with emphasis on the differences from the other embodiments, and the same similar parts between the various embodiments may be referred to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method sections disclosed in the embodiments, the description of the method sections may be referred to for relevance.
Those of skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. The skilled artisan may use different methods for each particular application to achieve the described functionality, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure. It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the embodiments disclosed herein, the disclosed methods, articles of manufacture (including but not limited to devices, apparatuses, etc.) may be practiced in other ways. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the units may be merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form. The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to implement the present embodiment. In addition, each functional unit in the embodiments of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the figures, operations or steps corresponding to different blocks may also occur in different orders than that disclosed in the description, and sometimes no specific order exists between different operations or steps. For example, two consecutive operations or steps may actually be performed substantially in parallel, they may sometimes be performed in reverse order, which may be dependent on the functions involved. Each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Claims (10)
1. A method for analyzing a time series of magnetic stripe cards, comprising:
performing periodic analysis processing on a time sequence generated by swiping the magnetic stripe card to generate a periodic sequence;
performing cycle prediction on the cycle sequence to obtain a target cycle predicted value;
and according to the target period predicted value, carrying out data bit judgment on the time sequence to obtain the data bit of the magnetic stripe card magnetic track.
2. The method of claim 1, wherein the periodically analyzing the time series generated by the swiping of the magnetic stripe card to generate the periodic series comprises:
extracting data bits in the time sequence and clock period values corresponding to the data bits;
under the condition that the data bit is bit 0, selecting a clock period value corresponding to the data bit as a target period value;
under the condition that the data bit is bit 1, selecting the sum of the clock period value corresponding to the data bit and the adjacent clock period value as a target period value;
and constructing a periodic sequence according to the respective target periodic values of different periodic numbers.
3. The method according to claim 1, wherein the performing the cycle prediction on the cycle sequence to obtain the target cycle prediction value includes:
Determining a historical period predicted value associated with the period sequence;
long-term prediction is carried out on the historical period predicted value, and a first period predicted value is obtained;
short-term prediction is carried out on the historical period predicted value, and a second period predicted value is obtained;
and carrying out weight calculation on the first cycle predicted value and the second cycle predicted value to obtain a target cycle predicted value.
4. The method of claim 3, wherein,
long-term prediction is carried out on the historical period predicted value to obtain a first period predicted value, and the method comprises the following steps: selecting a history period predicted value of a long period to perform straight line fitting or polynomial fitting to obtain a fitting straight line of the period number and the period predicted value; determining a first cycle predicted value based on the fitted line according to the current cycle number; and/or the number of the groups of groups,
short-term prediction is carried out on the historical period predicted value, and a second period predicted value is obtained; selecting a history period predicted value of a short period to perform curve fitting, and obtaining a fitting curve of the period number and the period predicted value; and determining a second cycle predicted value based on the fitted curve according to the current cycle number.
5. The analysis method according to claim 3, wherein weighting the first cycle prediction value and the second cycle prediction value to obtain the target cycle prediction value includes:
Calculating a target period predicted value according to the following formula:
，/>；
wherein,for the target period prediction value, +.>Representing a first cycle predicted value, a second cycle predicted value and an actual cycle value, respectively, +.>Indicating error, & lt>Respectively representing a first weight value, a second weight value, a third weight value and a fourth weight value; or,
calculating a target period predicted value according to the following formula:
，/>；
wherein,for the target period prediction value, +.>Representing a first cycle predicted value, a second cycle predicted value and an actual cycle value, respectively, +.>Respectively representing a first weight value, a second weight value and a third weight value.
6. The method of claim 5, wherein,
the first weight value is determined as follows: determining a first weight value according to the interference degree of the time sequence; and/or the number of the groups of groups,
the second weight value is determined as follows: and determining a second weight value according to the card swiping speed of the magnetic stripe card.
7. The method of any one of claims 1 to 6, wherein determining the data bits of the magnetic stripe card track based on the target period prediction value and the time series comprises:
determining a first judgment threshold of bit 0 according to the target period predicted value;
Determining a second judgment threshold of the bit 1 according to the target period predicted value;
and carrying out data bit judgment on the time sequence according to the first judgment threshold and the second judgment threshold to obtain the data bit of the magnetic stripe card track.
8. The method of any one of claims 1 to 6, wherein determining the data bits of the magnetic stripe card track based on the target period prediction value and the time series comprises:
determining a third judgment threshold of the interference signal according to the target period predicted value;
under the condition that a suspected interference signal exists in the time sequence, acquiring a current time stamp of the suspected interference signal;
and under the condition that the current time stamp is smaller than a third judgment threshold, determining the suspected interference signal as the interference signal.
9. An analysis device for a magnetic stripe card time series, comprising a processor and a memory storing program instructions, wherein the processor is configured to perform the analysis method for a magnetic stripe card time series of any one of claims 1 to 8 when the program instructions are executed.
10. A card reader, comprising:
a card swiping machine body;
the device for analyzing the time series of magnetic stripe cards of claim 9 mounted to the card reader body.
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