CN117708863B - Equipment data encryption processing method based on Internet of things - Google Patents
Equipment data encryption processing method based on Internet of things Download PDFInfo
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Abstract
The invention discloses a device data encryption processing method based on the Internet of things, which belongs to the technical field of data encryption and comprises the following steps: s1, acquiring the latest browsing records of a user, and acquiring a plurality of historical browsing records of the user and browsing behaviors of each historical browsing record from mobile terminal equipment; s2, determining a browsing heat value of the latest browsing record; and S3, generating an encryption key for the user according to the browsing hotness value of the latest browsing record, and carrying out encryption processing on the latest browsing record of the user by using the encryption key. The invention can comprehensively process the latest browsing record and a plurality of historical browsing records of the user, does not depend on the latest browsing record to determine the encryption key, comprehensively considers the whole browsing trace of the user, combines the browsing times and the browsing duration of the user browsing record, more accurately generates the targeted encryption key and improves the security level of encryption.
Description
Technical Field
The invention belongs to the technical field of data encryption, and particularly relates to a device data encryption processing method based on the Internet of things.
Background
Searching and browsing by using mobile terminals (such as mobile phones or tablets) are increasingly popular, and people feel worry about safety of browsing traces on the mobile terminals: browsing records stored on a public platform may be compromised by hacking and theft from inside. Encrypting a user's browsing records is an urgent problem to be solved.
Disclosure of Invention
The invention provides a device data encryption processing method based on the Internet of things in order to solve the problems.
The technical scheme of the invention is as follows: the device data encryption processing method based on the Internet of things comprises the following steps:
s1, acquiring the latest browsing records of a user, and acquiring a plurality of historical browsing records of the user and browsing behaviors of each historical browsing record from mobile terminal equipment;
S2, determining a browsing heat value of the latest browsing record according to the latest browsing record of the user, a plurality of historical browsing records and browsing behaviors of each historical browsing record;
And S3, generating an encryption key for the user according to the browsing hotness value of the latest browsing record, and carrying out encryption processing on the latest browsing record of the user by using the encryption key.
Further, in S1, the browsing behavior includes a browsing duration of each history browsing record.
Further, S2 comprises the following sub-steps:
S21, calculating the text similarity between each historical browsing record and the latest browsing record by using a WMD algorithm, and taking all the historical browsing records with the text similarity greater than 0.5 as a reference browsing record set;
s22, determining a time length label value of a reference browsing record set;
S23, constructing a browsing duration matrix according to the duration label value of the reference browsing record set and the browsing duration of the latest browsing record;
S24, determining a browsing heat value of the latest browsing record according to the browsing time length matrix.
The beneficial effects of the above-mentioned further scheme are: in the invention, the WMD algorithm is an algorithm for measuring the similarity of texts by calculating the distance between words between texts on the basis of word2 vec. The method comprises the steps of utilizing a WMD algorithm to obtain historical browsing records related to the latest browsing record content, calculating a time length label value according to the browsing times and the browsing time lengths of the historical browsing records, and integrating the time length label value with the browsing time length of the latest browsing record to construct a browsing time length matrix, wherein the browsing condition of the content related to the latest browsing record can be effectively reflected by the matrix.
Further, in S22, the calculation formula of the time length label value T 0 of the reference browse record set is: ; wherein t n_m represents the M-th browsing duration of the N-th historical browsing record in the reference browsing record set, M represents the browsing times of the historical browsing records in the reference browsing record set, and N represents the number of the historical browsing records in the reference browsing record set.
Further, in S23, the expression of the browsing duration matrix X is:
，/>，/> ; where w 0 represents the weight of the reference browsing record set, w 1 represents the weight of the latest browsing record, T 0 represents the time length tag value of the reference browsing record set, T 1 represents the browsing time length of the latest browsing record, T max represents the maximum browsing time length in the reference browsing record set, and T min represents the minimum browsing time length in the reference browsing record set.
Further, in S24, the specific method for determining the browsing heat value of the latest browsing record is as follows: singular value decomposition is carried out on the browsing duration matrix, and the singular value obtained by the singular value decomposition is used as the browsing heat value of the latest browsing record.
Further, S3 comprises the following sub-steps:
s31, preprocessing the latest browsing record of the user;
s32, extracting keywords of the latest browsing record after pretreatment as a first target field, and extracting words with highest word frequency in the latest browsing record after pretreatment as a second target field;
S33, determining a browsing content preference value according to the first target field and the second target field;
And S34, generating an encryption key for the user according to the browsing content preference value and the browsing heat value of the latest browsing record, and carrying out encryption processing on the latest browsing record of the user by utilizing the encryption key.
The beneficial effects of the above-mentioned further scheme are: in the invention, because the latest browsing record of the user is preprocessed (such as removing stop words, punctuation marks and the like), the keywords of the browsing content in the latest browsing record of the user and the word with the highest word frequency are used as target fields, the two target fields can better reflect the browsing preference of the user, and then the encryption key can be generated in a targeted way by combining the browsing heat value of the user and the identity of the user, so that the encryption grade is improved.
Further, in S33, the calculation formula of the browsing content preference value L is:
; in the formula, S represents the number of words of the latest browsing record after preprocessing, U represents the word vector of the first target field, V represents the word vector of the second target field, and exp (-) represents an exponential function.
Further, in S34, the expression of the encryption key G is:
; in the formula, I represents an identity corresponding to the latest browsing record of the user, L represents a browsing content preference value, hash (·) represents a hash function, and x represents a browsing heat value of the latest browsing record.
The beneficial effects of the invention are as follows: the invention can comprehensively process the latest browsing record and a plurality of historical browsing records of the user, does not depend on the latest browsing record to determine the encryption key, comprehensively considers the whole browsing trace of the user, combines the browsing times and the browsing duration of the user browsing record, more accurately generates the targeted encryption key and improves the security level of encryption.
Drawings
Fig. 1 is a flowchart of a device data encryption processing method based on the internet of things.
Detailed Description
Embodiments of the present invention are further described below with reference to the accompanying drawings.
As shown in fig. 1, the invention provides a device data encryption processing method based on the internet of things, which comprises the following steps:
s1, acquiring the latest browsing records of a user, and acquiring a plurality of historical browsing records of the user and browsing behaviors of each historical browsing record from mobile terminal equipment;
S2, determining a browsing heat value of the latest browsing record according to the latest browsing record of the user, a plurality of historical browsing records and browsing behaviors of each historical browsing record;
And S3, generating an encryption key for the user according to the browsing hotness value of the latest browsing record, and carrying out encryption processing on the latest browsing record of the user by using the encryption key.
In the embodiment of the present invention, in S1, the browsing behavior includes a browsing duration of each history browsing record.
In an embodiment of the present invention, S2 comprises the following sub-steps:
S21, calculating the text similarity between each historical browsing record and the latest browsing record by using a WMD algorithm, and taking all the historical browsing records with the text similarity greater than 0.5 as a reference browsing record set;
s22, determining a time length label value of a reference browsing record set;
S23, constructing a browsing duration matrix according to the duration label value of the reference browsing record set and the browsing duration of the latest browsing record;
S24, determining a browsing heat value of the latest browsing record according to the browsing time length matrix.
In the invention, the WMD algorithm is an algorithm for measuring the similarity of texts by calculating the distance between words between texts on the basis of word2 vec. The method comprises the steps of utilizing a WMD algorithm to obtain historical browsing records related to the latest browsing record content, calculating a time length label value according to the browsing times and the browsing time lengths of the historical browsing records, and integrating the time length label value with the browsing time length of the latest browsing record to construct a browsing time length matrix, wherein the browsing condition of the content related to the latest browsing record can be effectively reflected by the matrix.
In the embodiment of the present invention, in S22, the calculation formula of the duration tag value T 0 of the reference browse record set is:
; wherein t n_m represents the M-th browsing duration of the N-th historical browsing record in the reference browsing record set, M represents the browsing times of the historical browsing records in the reference browsing record set, and N represents the number of the historical browsing records in the reference browsing record set.
In the embodiment of the present invention, in S23, the expression of the browsing duration matrix X is:
，/>，/> ; where w 0 represents the weight of the reference browsing record set, w 1 represents the weight of the latest browsing record, T 0 represents the time length tag value of the reference browsing record set, T 1 represents the browsing time length of the latest browsing record, T max represents the maximum browsing time length in the reference browsing record set, and T min represents the minimum browsing time length in the reference browsing record set.
In the embodiment of the present invention, in S24, a specific method for determining the browsing popularity value of the latest browsing record is as follows: singular value decomposition is carried out on the browsing duration matrix, and the singular value obtained by the singular value decomposition is used as the browsing heat value of the latest browsing record.
In an embodiment of the present invention, S3 comprises the following sub-steps:
s31, preprocessing the latest browsing record of the user;
s32, extracting keywords of the latest browsing record after pretreatment as a first target field, and extracting words with highest word frequency in the latest browsing record after pretreatment as a second target field;
S33, determining a browsing content preference value according to the first target field and the second target field;
And S34, generating an encryption key for the user according to the browsing content preference value and the browsing heat value of the latest browsing record, and carrying out encryption processing on the latest browsing record of the user by utilizing the encryption key.
In the invention, because the latest browsing record of the user is preprocessed (such as removing stop words, punctuation marks and the like), the keywords of the browsing content in the latest browsing record of the user and the word with the highest word frequency are used as target fields, the two target fields can better reflect the browsing preference of the user, and then the encryption key can be generated in a targeted way by combining the browsing heat value of the user and the identity of the user, so that the encryption grade is improved.
In the embodiment of the present invention, in S33, the calculation formula of the browsing content preference value L is:
; in the formula, S represents the number of words of the latest browsing record after preprocessing, U represents the word vector of the first target field, V represents the word vector of the second target field, and exp (-) represents an exponential function.
In the embodiment of the present invention, in S34, the expression of the encryption key G is:
; in the formula, I represents an identity corresponding to the latest browsing record of the user, L represents a browsing content preference value, hash (·) represents a hash function, and x represents a browsing heat value of the latest browsing record.
Those of ordinary skill in the art will recognize that the embodiments described herein are for the purpose of aiding the reader in understanding the principles of the present invention and should be understood that the scope of the invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific modifications and combinations from the teachings of the present disclosure without departing from the spirit thereof, and such modifications and combinations remain within the scope of the present disclosure.
Claims (2)
1. The equipment data encryption processing method based on the Internet of things is characterized by comprising the following steps of:
s1, acquiring the latest browsing records of a user, and acquiring a plurality of historical browsing records of the user and browsing behaviors of each historical browsing record from mobile terminal equipment;
S2, determining a browsing heat value of the latest browsing record according to the latest browsing record of the user, a plurality of historical browsing records and browsing behaviors of each historical browsing record;
S3, generating an encryption key for the user according to the browsing hotness value of the latest browsing record, and carrying out encryption processing on the latest browsing record of the user by using the encryption key;
the step S2 comprises the following substeps:
S21, calculating the text similarity between each historical browsing record and the latest browsing record by using a WMD algorithm, and taking all the historical browsing records with the text similarity greater than 0.5 as a reference browsing record set;
s22, determining a time length label value of a reference browsing record set;
S23, constructing a browsing duration matrix according to the duration label value of the reference browsing record set and the browsing duration of the latest browsing record;
s24, determining a browsing heat value of the latest browsing record according to the browsing time length matrix;
In S22, the calculation formula of the time length label value T 0 of the reference browse record set is as follows: ; wherein t n_m represents the M-th browsing duration of the N-th historical browsing record in the reference browsing record set, M represents the browsing times of the historical browsing records in the reference browsing record set, and N represents the number of the historical browsing records in the reference browsing record set;
in S23, the expression of the browsing duration matrix X is: ，/>， ; wherein w 0 represents the weight of the reference browsing record set, w 1 represents the weight of the latest browsing record, T 0 represents the time length label value of the reference browsing record set, T 1 represents the browsing time length of the latest browsing record, T max represents the maximum browsing time length in the reference browsing record set, and T min represents the minimum browsing time length in the reference browsing record set;
in S24, the specific method for determining the browsing heat value of the latest browsing record is as follows: singular value decomposition is carried out on the browsing duration matrix, and a singular value obtained by the singular value decomposition is used as a browsing heat value of the latest browsing record;
The step S3 comprises the following substeps:
s31, preprocessing the latest browsing record of the user;
s32, extracting keywords of the latest browsing record after pretreatment as a first target field, and extracting words with highest word frequency in the latest browsing record after pretreatment as a second target field;
S33, determining a browsing content preference value according to the first target field and the second target field;
S34, generating an encryption key for the user according to the browsing content preference value and the browsing heat value of the latest browsing record, and carrying out encryption processing on the latest browsing record of the user by utilizing the encryption key;
In S33, the calculation formula of the browsing content preference value L is: ; wherein S represents the number of words of the latest browsing record after preprocessing, U represents the word vector of the first target field, V represents the word vector of the second target field, exp (-) represents an exponential function;
In S34, the expression of the encryption key G is: ; in the formula, I represents an identity corresponding to the latest browsing record of the user, L represents a browsing content preference value, hash (·) represents a hash function, and x represents a browsing heat value of the latest browsing record.
2. The method for encrypting device data based on the internet of things according to claim 1, wherein in S1, the browsing behavior includes a browsing duration of each history browsing record.
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