CN110188557B - Information hiding method based on big data search and robot system - Google Patents
Information hiding method based on big data search and robot system Download PDFInfo
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- CN110188557B CN110188557B CN201910455279.5A CN201910455279A CN110188557B CN 110188557 B CN110188557 B CN 110188557B CN 201910455279 A CN201910455279 A CN 201910455279A CN 110188557 B CN110188557 B CN 110188557B
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Abstract
An information hiding method and a robot system based on big data search, comprising: and searching out first information with high matching degree with the secret information from the big data, acquiring the position of the first information in the big data as a first position, and taking the difference between the secret information and the first information as second information. According to the method and the system, the secret information is hidden in the first information in the big data, so that the data volume of information hiding is not limited, meanwhile, the first information originally exists in the big data, the concealment is extremely strong, the information is difficult to break, and therefore the capacity and the safety of information hiding are improved.
Description
Technical Field
The present invention relates to the field of information technologies, and in particular, to an information hiding method and a robot system.
Background
Information hiding technology (Information Hiding), i.e. information hiding, plays an important role in protecting information from damage in future networks, which is a way to hide confidential information from adversaries in large amounts of information. Information hiding methods mainly include steganography, digital watermarking technology, visual passwords, latent channels, hiding protocols and the like.
In the process of implementing the present invention, the inventor finds that at least the following problems exist in the prior art: in the existing information hiding technology, the complexity and difficulty of analyzing and mining secret information from a carrier object and a disguised object are limited because the data volume of the carrier object and the disguised object is limited, so that the secret information is possibly cracked, and the information hiding safety is not high. Meanwhile, due to the limited data volume of the carrier object and the disguised object, a large amount of secret information cannot be hidden.
Accordingly, the prior art is still in need of improvement and development.
Disclosure of Invention
Based on the above, it is necessary to provide an information hiding method and a robot system based on big data search to solve the disadvantages of limited data size and easy cracking of information hiding in the prior art.
In a first aspect, an embodiment of the present invention provides an information hiding method, including:
and a data searching step: searching out first information with high matching degree with the secret information from big data;
position acquisition: acquiring the position of the first information in big data as a first position;
and a difference calculating step: the difference between the secret information and the first information is taken as second information.
Preferably, the method comprises the steps of,
the data searching step specifically comprises the following steps:
information segmentation: splitting the secret information into a plurality of partial secret information;
and a multi-data searching step: searching out a plurality of first information with high matching degree with a plurality of part of secret information from big data respectively;
the step of obtaining the position specifically includes:
a multi-position acquisition step: acquiring a plurality of positions of a plurality of first information in big data as a plurality of first positions;
the difference calculation step specifically comprises the following steps:
a multi-difference calculating step: corresponding differences between the plurality of secret information and the plurality of first information are taken as a plurality of second information.
Preferably, the difference calculating step further includes:
the multiple hiding execution steps are as follows: calculating a plurality of groups of first position and second information according to the first information;
and an authorization information sending step: and transmitting at least one group of the first position and the second information to a user.
In a second aspect, an embodiment of the present invention provides an information extraction method, including:
a first information extraction step: extracting first information from a first location in the big data;
secret information generation step: secret information is generated from the first information and the second information.
Preferably, the first information extraction step specifically includes:
multi-information extraction: extracting a plurality of first information from a plurality of first locations in the big data;
the secret information generation step specifically includes:
a multi-part secret information generation step: generating a plurality of partial secret information according to a plurality of the first information and a plurality of corresponding second information;
secret information generation step: and synthesizing the plurality of partial secret information to obtain secret information.
Preferably, the secret information generating step further includes:
the multi-time extraction execution step: acquiring a plurality of sets of secret information through a plurality of sets of first positions and second information;
and secret information screening: receiving verification information, and selecting secret information consistent with the verification information from a plurality of groups of secret information;
secret information transmission step: and sending the secret information to a user.
In a third aspect, an embodiment of the present invention provides an information hiding and extracting method, where the method includes the information hiding method and the information extracting method.
In a fourth aspect, an embodiment of the present invention provides an information hiding system, including:
and a data searching module: searching out first information with high matching degree with the secret information from big data;
and a position acquisition module: acquiring the position of the first information in big data as a first position;
the difference calculation module: the difference between the secret information and the first information is taken as second information.
Preferably, the method comprises the steps of,
the data searching module specifically comprises:
and the information segmentation module is used for: splitting the secret information into a plurality of partial secret information;
a multi-data search module: searching out a plurality of first information with high matching degree with a plurality of part of secret information from big data respectively;
the position acquisition module specifically comprises:
a multi-position acquisition module: acquiring a plurality of positions of a plurality of first information in big data as a plurality of first positions;
the difference calculation module specifically comprises:
the multi-difference calculation module: corresponding differences between the plurality of secret information and the plurality of first information are taken as a plurality of second information.
Preferably, the difference calculating module further comprises:
the multiple hiding execution module: calculating a plurality of groups of first position and second information according to the first information;
the authorization information sending module: and transmitting at least one group of the first position and the second information to a user.
In a fifth aspect, an embodiment of the present invention provides an information extraction system, including:
a first information extraction module: extracting first information from a first location in the big data;
a first information generation module: secret information is generated from the first information and the second information.
Preferably, the first information extraction module specifically includes:
the multi-information extraction module: extracting a plurality of first information from a plurality of first locations in the big data;
the first information generating module specifically includes:
a multipart secret information generation module: generating a plurality of partial secret information according to a plurality of the first information and a plurality of corresponding second information;
secret information generation module: and synthesizing the plurality of partial secret information to obtain secret information.
Preferably, the secret information generating module further comprises:
the multi-time extraction execution module is as follows: acquiring a plurality of sets of secret information through a plurality of sets of first positions and second information;
secret information screening module: receiving verification information, and selecting secret information consistent with the verification information from a plurality of groups of secret information;
secret information sending module: and sending the secret information to a user.
In a sixth aspect, an embodiment of the present invention provides an information hiding and extracting system, where the system includes the information hiding system and the information extracting system.
In a seventh aspect, an embodiment of the present invention provides a robot system in which the information hiding system according to the fourth aspect and the information extracting system according to the fifth aspect are respectively configured.
The embodiment of the invention has the beneficial effects that:
1. the information hiding technology based on big data search has the advantages that the complexity and difficulty of analyzing and mining secret information from the carrier object and the disguised object with extremely large data volume are extremely high as a 'sea fishing needle', so that the secret information is extremely unlikely to be cracked, and the information hiding safety is extremely high. Meanwhile, due to the large data volume of the carrier object and the disguised object, a large amount of secret information can be hidden.
2. Since the authority is possessed by the big data, but the first position and the second information are not known by the person who does not possess the authority to the secret information, the secret information cannot be extracted by the big data, so that the security of the secret information is ensured.
3. Since the first information is data having the highest degree of matching with the secret information, the difference between the first information and the secret information is small, and thus the data amount of the second information is small; meanwhile, the first position is the position or the number corresponding to the first information, so that the data size of the first position is small; therefore, the user can extract the secret information from the big data through synthesis only by sending the first position and the second information with small data quantity to the user with the authority to the secret information, and the network cost, the storage cost and the calculation cost are very low.
The information hiding method and the robot system based on big data search provided by the embodiment of the invention comprise the following steps: and searching out first information with high matching degree with the secret information from the big data, acquiring the position of the first information in the big data as a first position, and taking the difference between the secret information and the first information as second information. According to the method and the system, the secret information is hidden in the first information in the big data, so that the data volume of information hiding is not limited, meanwhile, the first information originally exists in the big data, the concealment is extremely strong, the information is difficult to break, and therefore the capacity and the safety of information hiding are improved.
Drawings
Fig. 1 is a flowchart of an information hiding method according to embodiment 1 of the present invention;
fig. 2 is a flowchart of an information extraction method provided in embodiment 3 of the present invention;
FIG. 3 is a flowchart of an information hiding and extracting method according to embodiment 5 of the present invention;
FIG. 4 is a schematic block diagram of an information hiding system according to embodiment 6 of the present invention;
fig. 5 is a schematic block diagram of an information extraction system according to embodiment 8 of the present invention;
fig. 6 is a schematic block diagram of an information hiding and extracting system according to embodiment 11 of the present invention.
Detailed Description
The following describes the technical scheme in the embodiment of the present invention in detail in connection with the implementation mode of the present invention. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Embodiment 1 provides an information hiding method, as shown in fig. 1, the method includes steps S110 to S170.
Secret information receiving step S110: accepting secret information to be hidden; for example, the information to be hidden is 100 first photos.
Data searching step S120: and searching out the first information y' with high matching degree with the secret information y from the big data. The secret information refers to information to be hidden, and can be words, passwords, images, graphics or sounds, and the like. For example, a second photograph having a degree of matching with 100 first photographs of more than 80% is searched out from big data (such as a google search or a whiteness search) as the first information. Wherein the first information may consist of one or more data in the big data, which may be distributed at any position in the big data. The high matching degree means that the matching degree of the secret information and the data is larger than a preset value, or the sequence number of the matching degree of the secret information and the data in the sequence from large to small of the matching degree of the secret information and the data in the large data is larger than a preset sequence number.
Position acquisition step S130: the position of the first information y' in the big data is acquired as the first position s. Preferably, the first position s includes a first start position s1 and a first end position s2, and y' is between the first start position s1 and the first end position s 2. For example, 100 network addresses of the 100 second photos are taken as the first location. The location comprises a storage location or a path or an index number or a sign, and the first information can be positioned from the big data through the location.
Difference calculation step S140: the difference between the first information y' and the secret information y is taken as the second information z. The difference between the first information and the first information is used as the second information, so that the first information can be recovered by the second information and the first information in the extraction stage. The formula: second information=f (secret information, first information), i.e. z=f (y, y'), where f is a function of the difference, and if the first information and the second information are both in digital format, the formula can be reduced to: second information = first information-first information. For example, a difference between 100 first photographs and corresponding second photographs is used as the second information, and for example, the pixel value of each first photograph may be subtracted from the pixel value of the corresponding second photograph to obtain the second information.
The multiple concealment performs step S150: S120-S140 can be adopted for multiple times to acquire multiple sets of first information which are not repeated and corresponding first position and second information, and multiple sets of first position and second information are sent to users with permission on secret information. For example, 3 non-duplicate groups of second photographs having a degree of matching with 100 first photographs of more than 80% are searched out from big data (such as a google search or a whiteness search) as 3 groups of first information.
An authorization information transmission step S160: at least one set of first locations s, second information z is sent to the user.
Verification information generation step S170: and sending part of information or attribute information of the secret information to a user who has authority to the secret information as verification information. For example, the last 20 pixel values of each first photo are used as the verification information, or the number of pixels of each first photo is used as the verification information.
Preferably, the second information and the check information can be inserted into the second position and the third position in the big data in the information hiding stage; therefore, the second information and the verification information are not required to be sent to the user, and only the second position and the third position are required to be sent to the user. And correspondingly extracting second information and check information from the second position and the third position in the big data in the information hiding stage.
A more specific embodiment: if the information to be hidden is 100 first photos, searching out second photos with the matching degree of more than 80% with the 100 first photos from big data (such as google searching pictures or whiteness searching pictures) to serve as first information, taking the download website of the 100 second photos as a first position, and taking the difference between the 100 first photos and the corresponding second photos as second information.
In embodiment 1, since the first information is the data having the highest matching degree with the secret information, the difference between the first information and the secret information is small, and thus the data amount of the second information is small; meanwhile, the first position is the position or the number corresponding to the first information, so that the data size of the first position is small; therefore, the user can extract the secret information from the big data through synthesis only by sending the first position and the second information with small data quantity to the user with the authority to the secret information, and the network cost, the storage cost and the calculation cost are very low.
Embodiment 2 provides a preferred information hiding method, according to the information hiding method described in embodiment 1, in combination with big data.
Step S110 includes an information segmentation step S111: the secret information y is split into a plurality of partial secret information y1, y2,..ym (m is the split number of copies).
Step S120 includes a multiple data search step S121: searching out a plurality of first information y1', y 2';
step S130 includes a multiple-position acquisition step S131: the plurality of first information y1', y 2'.
Step S140 includes a multi-difference calculation step S141: the plurality of first information y1', y 2'. Wherein z1=f (y 1, y1 '), z2=f (y 2, y2 '), & ltzm=f (ym, ym ').
The main beneficial effects of embodiment 2 are: the secret information is split into different parts and then converted, so that all parts of the secret information cannot be recovered even if part of the secret information is cracked, and further the secret information cannot be recovered, and the safety and the cracking difficulty of the secret information are further improved.
Since the principle of solving the problem by the system described below is similar to that of the method described above, the implementation of the system described below can be referred to the implementation of the method described above, and the repetition is omitted.
Since the principle of solving the problem by the system described below is similar to that of the method described above, the implementation of the system described below can be referred to the implementation of the method described above, and the repetition is omitted.
Examples 3 and 4 are information extraction methods corresponding to examples 1 and 2, respectively. The preferred embodiments and beneficial effects of embodiments 3 and 4 are similar to those of embodiments 1 and 2, respectively, and will not be described again.
Embodiment 3 provides an information extraction method including steps S210 to S270, as shown in fig. 2.
Authorization information acquisition step S210: at least one set of first location s, second information z is accepted. The first location s and the second information z are typically received from the user terminal via the network.
A first information extraction step S220: the first information y' is extracted from the first location s in the big data. For example, 100 second photos are downloaded from 100 network addresses in the first location as the first information.
Secret information generation step S230: secret information y is generated from the first information y' and the second information z. Since in the hidden phase the second information=f (secret information, first information), where f is a function that finds the difference between the secret information and the first information, the secret information is calculated by substituting the second information and the first information into this formula when recovering the secret information. When the secret information, the first information is a number, the secret information=the first information+the second information. For example, the pixel value of each first photo is obtained by adding the pixel value of each second photo in the first information to the corresponding pixel value in the second information.
The multiple extraction execution step S240: s220 to S230 may be employed multiple times to acquire multiple sets of secret information through multiple sets of first location and second information.
Information verification S250: secret information consistent with the verification information is selected from the plurality of sets of secret information.
Secret information selection step S260: when the secret information matched with the verification information in the step S'6 has a plurality of groups, if each group of secret information is the same as the other K groups of secret information, the group of secret information corresponding to the maximum K value is selected. For example, the 1 st group and the 2 nd group are identical, the 3 rd group is different from the other 2 nd group, that is, the 1 st group is identical to the other 1 st group, the 2 nd group is identical to the other 1 st group, the 3 rd group is identical to the other 0 th group, and the 1 st group or the 2 nd group is selected.
Secret information transmission step S270: the secret information is transmitted to a user who has authority for the secret information.
Embodiment 4 provides an information extraction method according to the information extraction method described in embodiment 3, in combination with big data.
Step S210 includes a multiple authorization information acquisition step S211: a plurality of first locations s1, s2, accepting user input, sm, a plurality of second information z1, z2, zm.
Step S220 includes a plurality of first information extraction steps S221: a plurality of first information y1', y 2'.
Step S230 includes a multi-secret information generation step S231: from the plurality of first information y1', y 2'. Wherein z1=f (y 1, y1 '), z2=f (y 2, y2 '), & ltzm=f (ym, ym ').
Step S230 includes a secret information generation step S232: the secret information y is synthesized from a plurality of pieces of partial secret information y1, y 2. Preferably, in the information hiding embodiment, the secret information y is equally divided into m copies as a character string, to be y1, y 2. Preferably, sequence numbers are extracted from the header of the respective partial secret information, e.g. 1 in 1y1 and 2 in y1,2y2 and m and ym in mym. Y1, y2, &..ym was combined according to the order of sequence numbers to give y.
The beneficial effects are that: the plurality of partial secret information is finally synthesized so that the secret information can be restored without loss.
Embodiment 5 provides an information hiding and extracting method, as shown in fig. 3, composed of the information hiding method of any one of embodiments 1 to 2 and the information extracting method of any one of embodiments 3 to 4.
Examples 6-10 are systems corresponding to examples 1-5, respectively. The preferred embodiments and advantageous effects of examples 6-10 are similar to those of examples 1-5, respectively, and are not repeated.
Embodiment 6 provides an information hiding system including modules 110 to 170 as shown in fig. 4.
Secret information receiving module 110: accepting secret information that needs to be hidden.
The data search module 120: and searching out the first information y' with high matching degree with the secret information y from the big data.
The position acquisition module 130: the position of the first information y' in the big data is acquired as the first position s.
The variance calculation module 140: the difference between the first information y' and the secret information y is taken as the second information z.
Multiple hidden execution module 150: S120-S140 can be adopted for multiple times to acquire multiple sets of first information which are not repeated and corresponding first position and second information, and multiple sets of first position and second information are sent to users with permission on secret information.
Authorization information sending module 160: at least one set of first locations s, second information z is sent to the user.
The verification information generation module 170: and sending part of information or attribute information of the secret information to a user who has authority to the secret information as verification information.
Embodiment 7 provides a preferred information hiding system according to the information hiding system described in embodiment 6, combined with big data.
The module 110 includes an information slicing module 111: the secret information y is split into a plurality of partial secret information y1, y2,..ym (m is the split number of copies).
The module 120 includes a multiple data search module 121: searching out a plurality of first information y1', y 2';
the module 130 includes a multi-location acquisition module 131: the plurality of first information y1', y 2'.
The module 140 includes a multi-variance calculation module 141: the plurality of first information y1', y 2'.
Examples 8 and 9 are information extraction systems corresponding to examples 6 and 7, respectively. The preferred embodiments and beneficial effects of examples 8 and 9 are similar to those of examples 6 and 7, respectively, and will not be described again.
Embodiment 8 provides an information extraction system, as shown in fig. 5, comprising modules 210 through 270.
Authorization information acquisition module 210: at least one set of first location s, second information z is accepted. The first location s and the second information z are typically received from the user terminal via the network.
The first information extraction module 220: the first information y' is extracted from the first location s in the big data. For example, 100 second photos are downloaded from 100 network addresses in the first location as the first information.
The secret information generation module 230: secret information y is generated from the first information y' and the second information z.
Multiple extraction execution module 240: s220 to S230 may be employed multiple times to acquire multiple sets of secret information through multiple sets of first location and second information.
Information verification S250: secret information consistent with the verification information is selected from the plurality of sets of secret information.
Secret information selection module 260: when the secret information matched with the verification information in the step S'6 has a plurality of groups, if each group of secret information is the same as the other K groups of secret information, the group of secret information corresponding to the maximum K value is selected.
Secret information transmission module 270: the secret information is transmitted to a user who has authority for the secret information.
Embodiment 9 provides an information extraction system according to the information extraction system of embodiment 8, in combination with big data.
The module 210 includes a multi-authorization information acquisition module 211: a plurality of first locations s1, s2, accepting user input, sm, a plurality of second information z1, z2, zm.
The module 220 includes a plurality of first information extraction modules 221: a plurality of first information y1', y 2'.
The module 230 includes a multi-secret information generation module 231: from the plurality of first information y1', y 2'.
The module 230 includes a secret information generation module 232: the secret information y is synthesized from a plurality of pieces of partial secret information y1, y 2.
Embodiment 10 provides an information hiding and extracting system composed of the information hiding system of any one of embodiments 6 to 7 and the information extracting system of any one of embodiments 8 to 9.
Embodiment 11 provides an information hiding and extracting robot system, as shown in fig. 6, composed of the information hiding system of any one of embodiments 1 to 5 and the information extracting system of any one of embodiments 6 to 10.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random-access Memory (Random Access Memory, RAM), or the like.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (8)
1. An information hiding method, the method comprising:
and a data searching step: searching out first information with high matching degree with secret information from big data; the high matching degree means that the matching degree of the secret information and the data is larger than a preset value, or the sequence number of the matching degree of the secret information and the data in the sequence from large to small of the matching degree of the secret information and the data in the large data is larger than a preset sequence number;
the first information consists of one or more data in big data, wherein the one or more data are distributed at any position in the big data;
position acquisition: acquiring the position of the first information in big data as a first position;
and a difference calculating step: taking the difference between the secret information and the first information as second information; second information=f (secret information, first information), where f is a function of the difference;
multiple sets of first information which is not repeated and corresponding first position and second information are acquired for multiple times, and the multiple sets of first position and second information are sent to a user with authority for secret information;
the method comprises an information extraction method and is characterized by comprising the following steps:
a first information extraction step: extracting first information from a first location in the big data;
secret information generation step: generating secret information according to the first information and the second information;
acquiring multiple sets of secret information through multiple sets of first positions and second information;
selecting secret information consistent with the verification information from a plurality of groups of secret information;
when the secret information matched with the verification information has a plurality of groups, if each group of secret information is the same as other K groups of secret information, selecting the group of secret information corresponding to the maximum K value.
2. The information hiding method according to claim 1, wherein,
the data searching step specifically comprises the following steps:
information segmentation: splitting the secret information into a plurality of partial secret information;
and a multi-data searching step: searching out a plurality of first information with high matching degree with a plurality of part of secret information from big data respectively; the step of obtaining the position specifically includes:
a multi-position acquisition step: acquiring a plurality of positions of a plurality of first information in big data as a plurality of first positions;
the difference calculation step specifically comprises the following steps:
a multi-difference calculating step: corresponding differences between the plurality of secret information and the plurality of first information are taken as a plurality of second information.
3. The information hiding method according to claim 1, wherein the difference calculating step further comprises, after:
the multiple hiding execution steps are as follows: calculating a plurality of groups of first position and second information according to the first information;
and an authorization information sending step: and transmitting at least one group of the first position and the second information to a user.
4. The information hiding method according to claim 1, wherein the first information extracting step specifically includes: multi-information extraction: extracting a plurality of first information from a plurality of first locations in the big data;
the secret information generation step specifically includes:
a multi-part secret information generation step: generating a plurality of partial secret information according to a plurality of the first information and a plurality of corresponding second information;
secret information generation step: and synthesizing the plurality of partial secret information to obtain secret information.
5. The information hiding method according to claim 1, wherein the secret information generating step further comprises, after:
the multi-time extraction execution step: acquiring a plurality of sets of secret information through a plurality of sets of first positions and second information;
and secret information screening: receiving verification information, and selecting secret information consistent with the verification information from a plurality of groups of secret information;
secret information transmission step: and sending the secret information to a user.
6. An information hiding and extracting method, characterized in that the method comprises the information hiding method as claimed in any one of claims 1-5.
7. An information hiding system, the system comprising:
and a data searching module: searching out first information with high matching degree with secret information from big data; the high matching degree means that the matching degree of the secret information and the data is larger than a preset value, or the sequence number of the matching degree of the secret information and the data in the sequence from large to small of the matching degree of the secret information and the data in the large data is larger than a preset sequence number;
the first information consists of one or more data in big data, wherein the one or more data are distributed at any position in the big data;
and a position acquisition module: acquiring the position of the first information in big data as a first position;
the difference calculation module: taking the difference between the secret information and the first information as second information; second information=f (secret information, first information), where f is a function of the difference;
multiple sets of first information which is not repeated and corresponding first position and second information are acquired for multiple times, and the multiple sets of first position and second information are sent to a user with authority for secret information;
the system comprises an information extraction system, characterized in that the system comprises:
a first information extraction module: extracting first information from a first location in the big data;
a first information generation module: generating secret information according to the first information and the second information;
acquiring multiple sets of secret information through multiple sets of first positions and second information;
selecting secret information consistent with the verification information from a plurality of groups of secret information;
when the secret information matched with the verification information has a plurality of groups, if each group of secret information is the same as other K groups of secret information, selecting the group of secret information corresponding to the maximum K value.
8. A robot system, wherein the robot is provided with the information hiding system according to claim 7.
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| CN107786555A (en) * | 2017-10-24 | 2018-03-09 | 大国创新智能科技(东莞)有限公司 | Information steganography method and system, information extracting method and system based on big data |
| CN108197488A (en) * | 2017-12-25 | 2018-06-22 | 大国创新智能科技(东莞)有限公司 | Information hiding, extracting method and system based on big data and neural network |
| US10275826B1 (en) * | 2008-05-16 | 2019-04-30 | The Pnc Financial Services Group, Inc. | Hidden money folders |
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| US10275826B1 (en) * | 2008-05-16 | 2019-04-30 | The Pnc Financial Services Group, Inc. | Hidden money folders |
| CN107786555A (en) * | 2017-10-24 | 2018-03-09 | 大国创新智能科技(东莞)有限公司 | Information steganography method and system, information extracting method and system based on big data |
| CN108197488A (en) * | 2017-12-25 | 2018-06-22 | 大国创新智能科技(东莞)有限公司 | Information hiding, extracting method and system based on big data and neural network |
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