CN116208331A - Password reminding method, device and equipment - Google Patents
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Abstract
The embodiment of the specification discloses a password reminding method, a password reminding device and password reminding equipment. The method comprises the following steps: acquiring data to be processed, wherein the data to be processed comprises password use information and/or account value of a user and/or preference information of the user for using the password and/or password-based time information; inputting the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method; and if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user. By adopting the password reminding method provided by the embodiment of the specification, the memory of the user on the password is enhanced through active reminding, and the password forgetting probability is reduced, so that the user experience of the user using password verification is improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a password reminding method, device and equipment.
Background
With the development of information and the internet, electronic commerce is increasingly used. In electronic commerce, password verification is one of the important ways to verify and check the identity. Although biological nuclear body technology based on modes such as fingerprint, face recognition and voice is rapidly developed, a verification mode adopting password verification is still widely applied, and the main reason is as follows: factors such as usage habit, usage scene, equipment and the like, for example, the fact that the PC end is difficult to collect fingerprints, the fact that the environment is noisy or crowd-intensive, and the fact that the face or voice is used for checking and checking the body is inconvenient.
In the conventional password verification method, the password is forgotten. Data shows that in e-commerce, the number of users who fail the business due to forgetting the password is tens to millions per day. This forgetting of the password results in a failure of the service, which on the one hand may bring a bad experience to the user and on the other hand may result in the user not using the service any more.
Based on this, in order to reduce the situation of forgetting the password in the existing password verification, a new method is required to reduce or reduce the password forgetting.
Disclosure of Invention
The embodiment of the specification provides a password reminding method, device and equipment, which are used for solving the following technical problems: in the password verification process, the situation of forgetting the password exists, so that the service is failed, bad experience is brought to the user, and even the user is not used any more.
In order to solve the above technical problems, the embodiments of the present specification are implemented as follows:
the password reminding method provided by the embodiment of the specification comprises the following steps:
acquiring data to be processed, wherein the data to be processed comprises password use information and/or account value of a user and/or preference information of the user for using the password and/or password-based time information;
inputting the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method;
and if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user.
The password reminding method provided by the embodiment of the specification comprises the following steps:
acquiring data to be processed, wherein the data to be processed comprises a current observation value and historical information of a user;
inputting the data to be processed into a password verification model to obtain a benefit value, wherein the password verification reminding model is a model which is obtained by training in advance based on an enhanced learning method, and the current observation value comprises password forgetting probability and/or preference information of the user using a password;
Determining whether a password verification prompt is needed to be carried out on the user based on the benefit value;
if the password verification reminding needs to be carried out on the user, the password verification reminding is pushed to the user.
The embodiment of the present specification provides a password reminding device, including:
the device comprises an acquisition module, a processing module and a processing module, wherein the data to be processed comprises password use information and/or user account value and/or user password use preference information and/or password-based time information;
the scoring module inputs the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model for scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method;
and the password modification reminding module is used for pushing a password modification reminder to the user if the password forgetting probability is greater than or equal to a preset forgetting probability value.
The embodiment of the present specification provides a password reminding device, including:
the device comprises an acquisition module, a processing module and a processing module, wherein the data to be processed comprises a current observation value and historical information of a user;
The profit module inputs the data to be processed into a password verification model to obtain a profit value, wherein the password verification reminding model is a model which is obtained by training in advance based on an enhanced learning method, and the current observation value comprises password forgetting probability and/or preference information of the user using passwords;
the decision module is used for determining whether the user needs to be subjected to password verification reminding based on the benefit value;
and the password verification module is used for pushing the password verification prompt to the user if the password verification prompt is needed to be carried out to the user.
An electronic device provided in an embodiment of the present disclosure includes:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring data to be processed, wherein the data to be processed comprises password use information and/or account value of a user and/or preference information of the user for using the password and/or password-based time information;
Inputting the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method;
and if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user.
An electronic device provided in an embodiment of the present disclosure includes:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring data to be processed, wherein the data to be processed comprises a current observation value and historical information of a user;
inputting the data to be processed into a password verification model to obtain a benefit value, wherein the password verification reminding model is a model which is obtained by training in advance based on an enhanced learning method, and the current observation value comprises password forgetting probability and/or preference information of the user using a password;
Determining whether a password verification prompt is needed to be carried out on the user based on the benefit value;
if the password verification reminding needs to be carried out on the user, the password verification reminding is pushed to the user.
The above-mentioned at least one technical scheme that this description embodiment adopted can reach following beneficial effect: according to the embodiment of the specification, the password reminding model is adopted, the password forgetting probability corresponding to the data to be processed is obtained, if the password forgetting probability is larger than or equal to the preset forgetting probability value, a password modifying reminder is pushed to a user to modify the password reminding, the memory of the user to the password is enhanced through active reminding, the password forgetting probability is reduced, and the user experience of the user using password verification is improved.
Drawings
In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some of the embodiments described in the present description, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a frame diagram of a password reminding method according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of another data reminding method according to an embodiment of the present disclosure;
fig. 3 is a frame diagram of a password reminding method according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a data reminding device according to an embodiment of the present disclosure;
fig. 5 is a schematic diagram of another data reminding device according to an embodiment of the disclosure.
Detailed Description
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
In the prior art, a platform or a website using password verification is generally provided with a design of 'retrieving a password' or 'modifying a password' or 'resetting a password', so that when a user forgets the password, a new password is obtained again. But this design pertains to user-initiated behavior of passively obtaining a new password. Since most users are not aware of forgetting the password, the forgotten password is found only when the password verification is performed, and thus the password verification requirement of a quick requirement scene or an instant requirement scene, such as the situation that the password is found to be forgotten when a movie ticket is purchased in a queuing, is not satisfied.
In the embodiments of the present disclosure, a password refers to a password that includes one or more characters, such as numeric characters and/or alphabetic characters and/or special characters. The combination of passwords and/or the number of digits of the passwords do not constitute a limitation of the present application.
Based on this, a new method is needed, which can remind the user of the password before the user forgets the password, so as to meet the password verification requirement of the quick demand scene or the instant demand scene.
Fig. 1 is a frame diagram of a password reminding method provided in an embodiment of the present disclosure, which specifically includes:
step S101: and acquiring data to be processed, wherein the data to be processed comprises password use information and/or account value of a user and/or preference information of the user for using the password and/or password-based time information.
In this embodiment of the present disclosure, the data to be processed is data of a user who needs to perform password verification, so as to reflect history information of the user performing password verification. The data to be processed is data related to a cryptographic check. In the implementation process, the data to be processed is password use information, and/or account value of the user, and/or preference information of the user for using the password, and/or password-based time information, and further comprises static information of the user.
In the embodiment of the present disclosure, in the data to be processed, the usage information of the password is based on an index formed by the user during the password verification process based on the password usage behavior. In a specific implementation process, the password use behavior of the user includes: the frequency of using the payment password, and/or the time of last using the password, and/or the time of last forgetting the password, and/or whether the last using the password forgets the password.
In this embodiment of the present disclosure, the account value of the user includes the number of cards bound by the account, and/or the transaction amount of the account, and/or the friend number of the account, and/or the frequency of use of the account.
In the embodiment of the present disclosure, in the data to be processed, the preference information of the user for using the password refers to personal preference of the user for using the password, and specifically may include a service scenario of using the password by the user and/or security preference of the user and/or transaction risk level of using the password by the user and/or equipment condition used for password verification.
In the embodiment of the present specification, the service scenario in which the user uses the password refers to the service scenario in which the user performs password verification. In the implementation process, the service environment of the user using the password comprises the following steps: a non-instant scene or an instant scene, such as: pre-paying water and electricity fees; instant scenes, for example: queuing to purchase movie tickets.
In the embodiment of the present specification, the user's security preference is to describe the user itself, so that some people are careful, habitually use passwords and replace the passwords, some people are random, the passwords can be very simple, and the information can be described through the historical operation behaviors of the user.
In the embodiment of the present specification, the risk level of the transaction by the user using the password refers to the risk level of the transaction, which is generally determined by a corresponding model or policy, for example, the transaction is inconsistent with the common usage of the user, the transaction device is inconsistent with the common usage of the user, the abnormal high-frequency operation is all high-risk transaction.
In the embodiment of the present specification, the device condition used for the password verification refers to whether the mobile terminal or the client terminal is used when the password verification is performed.
In the present description, password-based time information refers to historical operations based on a user using a password, and/or payment liveness, and/or payment patterns. In an implementation, the password-based time information includes: days of transaction, and/or days of login or password or binding, and/or payment transaction, and/or days of high-volume transaction.
In this embodiment of the present disclosure, in the data to be processed, the static information of the user is an account basic attribute of the user, which is used to reflect the basic characteristics of the user or the account, including the age of the user and/or the opening time of the account, and/or the authentication time of the account, and/or the type of the account. The types of accounts include, in particular, whether the account is an enterprise account or a personal account, and/or whether the account is used by a single person or multiple persons.
Step S103: inputting the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method.
In the embodiment of the present specification, the password alert model is a model that scores the password forgetting probability. The password reminding model is a model which is obtained by training in advance based on historical data and a supervised learning method.
The supervised learning approach is a machine learning task that extrapolates functions from a labeled training dataset.
In the embodiment of the present specification, when training the password alert model, sample tag data of the password alert model includes black sample tag data and white sample tag data, wherein,
The black sample tag data is data of a user who carries out password resetting or password searching or losing in the password using process in the historical data;
the white sample tag data is data of a user who uses a password in the history data and inputs the password without errors.
In one embodiment of the present specification, the black sample tag data is data of a user who performs a business process by searching a password through a port in history data, resetting the password,
or (b)
In the history data, the data of the user lost in the process of searching the password,
or (b)
In the history data, the data of the user lost in the process of using the password is displayed.
In the specific implementation process, the historical data is searched for the password through the port, and the port can be a payment port or a setting port;
the black label data is marked 1 and the white label data is marked 0.
In the embodiment of the present disclosure, the statistical period of the history data may be selected from 3 months to 6 months, and the statistical period of the history data is not particularly limited to the present application.
In the embodiment of the present specification, the password alert model is a model obtained based on a forgetting function and user-related information, wherein the forgetting function is a time-based function, and the user-related information includes static information of a user and/or use information of a password and/or account information of the user and/or preference information of the user to use the password and/or time information based on the password.
In the embodiment of the specification, the forgetting function and the user related information are respectively used as the input of the model to train the password reminding model. The forgetting function is used for reprocessing and strengthening the time-related data and judging the fading or weakening degree of the time-related data in a specific time length.
In the present embodiment, the forgetting function x1=f (t), where t is time;
x2 is user-related information, then the password forgetting probability y=f (x 1, x 2), that is, the password forgetting probability is a probability obtained based on the forgetting function and the user-related information.
Step S105: and if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user.
By adopting the method provided by the steps, the password forgetting probability corresponding to the data to be processed can be obtained, and whether the password modification reminding needs to be pushed to the user is further judged according to the preset forgetting probability value.
If the password forgetting probability is lower than a preset forgetting probability value, pushing a password modification reminder to a user is not needed; and if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user so as to prompt the user to modify the password prompt.
In the embodiment of the present specification, the selection of the preset forgetting probability value is based on: ensuring that the user has a good experience, and/or funding situation.
In one embodiment of the present description, the preset forgetting probability value is 0.8.
After receiving the pushed password modification prompt, the user can autonomously decide whether password modification is needed or not, and can set the system to be necessary to carry out password modification.
By adopting the data reminding method provided by the embodiment of the specification, the password modification reminding can be actively pushed during the login of the user, the password modification reminding is carried out on the user, and the password verification experience of the user is enhanced.
Fig. 2 is a schematic diagram of another data reminding method according to an embodiment of the present disclosure, which specifically includes:
step S201: and acquiring data to be processed, wherein the data to be processed comprises password use information and/or account value of a user and/or preference information of the user for using the password and/or password-based time information.
Step S203: inputting the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method.
Step S205: and if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user.
In the embodiment of the specification, a user pushing a password modification reminder belongs to a user who easily forgets the password, and in order to strengthen the memory of the user on the password, thereby avoiding the situation of forgetting the password, after pushing the password modification reminder to the user, the password verification reminder needs to be pushed to the user.
Step S207: and obtaining a benefit value by utilizing a password verification model based on a current observation value and historical information of a user, wherein the password verification model is a model which is obtained by training in advance based on an enhanced learning method, and the current observation value comprises the password forgetting probability and/or preference information of the user using a password.
In this embodiment of the present disclosure, the current observation value is a password forgetting probability of the user in the current transaction or the current transaction, and/or preference information of the user to use the password.
Reinforcement learning is a machine learning method that enables agents to learn through trial and error based on their own actions and experience feedback in an interactive environment.
The basic idea of reinforcement learning is: tuple(s) consisting of (state, behavior, rewards, next state) t ,a t ,r t +1 ,s t+1 ) Training for samplesScouring, wherein s t A is the current state, a t For the action executed in the current state, r t+1 To execute rewards after action s t+1 The next state.
In the embodiment of the present specification, the obtaining of the password verification model includes:
taking the history information, the data to be processed and the password forgetting probability as state data;
whether password verification is used or not is taken as a decision variable;
and calculating a benefit function corresponding to the state transfer function formed by the state data and the decision variables, and pushing a password verification reminder to the user when the benefit function meets a preset condition.
In one embodiment of the present description, the status data specifically includes:
presetting history information and current observation values in a history period, wherein,
the history information in the preset history period comprises a password verification and result sequence,
the observations include current transaction password forgetting probabilities, and/or user preference information for using passwords.
It should be noted that the preset history period may be a certain preset period of time, or may be an average period of time for password use. In the specific implementation process, the preset history period can be set in units of weeks or days. The predetermined history period may be 1 week, or 30 days, or 90 days, or 180 days. The specific length of the preset history period is not limited to this application.
In the embodiment of the specification, the password verification in the history information refers to a decision of whether the user is required to input a password for verification at each time t, and is pushed to the user by the service end; the result sequence in the history information is the result of the password verification performed by the user, namely the feedback information. The password verification and result sequence is in a sequence shape in the whole time interval.
In one embodiment of the present description, the state transfer function is an estimate of the cryptographic verification result,
S t+1 ＝p t ＝P(a t |S t ,O t )
wherein a is t Indicating whether or not to use the password, O t S is the current observed value t For history information, p t Is the password forgetting probability.
In the examples of the present specification, a t Belonging to the time-dependent sequence, it may be in days or hours, depending on the traffic scenario.
The state transfer function is a probability function related to actions in the current state, and is an estimated value of the password verification result, wherein a probability value 1 represents the success of the password verification, and a probability value 0 represents the failure of the password verification.
In one embodiment of the present description, the benefit function is a benefit or loss corresponding to success or failure of the password verification in the current business scenario,
r t ＝k y *p t
wherein r is t As a benefit function, k t For risk level, p t Is the password forgetting probability.
It should be noted that the benefit function considers the current risk level, and/or user security preference, and/or transaction scenario, and the benefit or loss corresponding to success or failure of the finally obtained password verification.
Based on the method provided by the embodiment of the specification, according to the fact that the corresponding value obtained by the benefit function is the benefit value, the benefit of carrying out or not carrying out the password verification reminding can be determined, and therefore whether the password verification reminding needs to be pushed to the user or not is determined.
Step S209: and determining whether the user needs to be subjected to password verification reminding based on the benefit value.
The benefit value obtained in the previous step is used for reflecting the benefit of carrying out password verification reminding or not, and whether the user needs to be subjected to verification reminding can be determined according to the benefit value.
Step S211: if the password verification reminding needs to be carried out on the user, the password verification reminding is pushed to the user.
In practical application, the password verification reminding method provided by the embodiment of the specification needs to comprehensively weigh time and business scenes, and can be applied to non-instant and micropayment scenes, such as pre-paying water and electricity fees, in a specific implementation process. By adopting the password verification reminding, the memory of the user to the password can be enhanced, so that the forgetting degree of the user to the password in the future is avoided or weakened.
By adopting the method provided by the embodiment of the specification, the password modification prompt can be actively pushed to the user, the memory of the user on the password is enhanced, the password forgetting probability is reduced, and the user experience of the user using password verification is improved; by adopting the password verification reminding, the memory of the user to the password can be enhanced, so that the forgetting degree of the user to the password in the future is avoided or weakened.
The embodiment of the specification also provides a password reminding method, as shown in fig. 3. Fig. 3 is a frame diagram of a password reminding method according to an embodiment of the present disclosure, where the password reminding method includes:
step S301: and acquiring data to be processed, wherein the data to be processed comprises the current observation value and the history information of the user.
In this embodiment of the present disclosure, the current observation value is a password forgetting probability of the user in the current transaction or the current transaction, and/or preference information of the user to use the password.
Step S303: inputting the data to be processed into a password verification model to obtain a benefit value, wherein the password verification reminding model is a model which is obtained by training in advance based on an enhanced learning method, and the current observation value comprises password forgetting probability and/or preference information of the user using a password;
Step S305: determining whether a password verification prompt is needed to be carried out on the user based on the benefit value;
step S307: if the password verification reminding needs to be carried out on the user, the password verification reminding is pushed to the user.
The foregoing details a data reminding method, and accordingly, the embodiment of the present disclosure further provides a data reminding device, as shown in fig. 4. Fig. 4 is a schematic diagram of a data reminding device according to an embodiment of the present disclosure, where the reminding device includes:
an obtaining module 401, configured to obtain data to be processed, where the data to be processed includes information about use of a password, and/or account value of a user, and/or preference information about use of the password by the user, and/or time information based on the password;
the scoring module 403 inputs the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model for scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method;
and the password modification reminding module 405 pushes a password modification reminder to the user if the password forgetting probability is greater than or equal to a preset forgetting probability value.
The reminding device comprises:
the profit module 407 obtains a profit value by using a password verification model based on a current observation value and historical information of a user, wherein the password verification model is a model obtained by training in advance based on an enhanced learning method, and the current observation value comprises the password forgetting probability and/or preference information of the user using a password
The decision module 409 determines, based on the benefit value, whether a password verification reminder is required for the user;
the password verification module 411 pushes the password verification reminder to the user if the password verification reminder is needed to be carried out to the user.
Further, the obtaining module 401 further includes:
the data to be processed further comprises static information of the user, wherein the static information comprises the age, and/or occupation, and/or account type, and/or authentication duration, and/or opening time of the user.
Further, the scoring module 403 specifically includes:
the password reminding model is a model obtained based on a forgetting function and user related information, wherein the forgetting function is a time-based function, and the user related information comprises static information of a user and/or use information of a password and/or account value of the user and/or preference information of the user for using the password and/or time information based on the password.
Sample data of the password alert model includes black sample tag data and white sample tag data, wherein,
the black sample tag data is data of a user who performs password resetting or password searching or losing in the password using process in the historical data;
the white sample tag data is data of a user who uses a password in the historical data and inputs the password without errors.
The black sample tag data is the data of the user who searches the password through the port in the history data and processes the business by resetting the password,
or (b)
In the history data, the data of the user lost in the process of searching the password,
or (b)
In the history data, the data of the user lost in the process of using the password is displayed.
Further, the decision module 407 specifically includes:
the training of the password verification model comprises the following steps:
taking the history information and the current observation value of the user as state data, wherein the history information of the user is the history information in a preset history period;
whether password verification is used or not is taken as a decision variable;
and calculating a benefit function corresponding to the state transfer function formed by the state data and the decision variables. The state transfer function is an estimate of the cryptographic verification result,
S t+1 ＝p t ＝P(a t |S t ,O t )
Wherein a is t Indicating whether or not to use the password, O t For the current observationValue, S t For history information, p t Is the password forgetting probability.
The profit function is the profit value corresponding to the success or failure of the password verification under the current business scene, the profit value is profit or loss,
r t ＝k t *p t
wherein r is t As a benefit function, k t For risk level, p t Is the password forgetting probability.
The embodiment of the present disclosure further provides another data reminding method, and accordingly, the embodiment of the present disclosure further provides another data reminding device, as shown in fig. 5. Fig. 5 is a schematic diagram of another data reminding device according to an embodiment of the disclosure, where the reminding device includes:
the obtaining module 501 is configured to obtain data to be processed, where the data to be processed includes a current observed value and history information of a user;
the profit module 503 inputs the data to be processed into a password verification model to obtain a profit value, wherein the password verification reminding model is a model which is obtained by training in advance based on an enhanced learning method, and the current observation value comprises password forgetting probability and/or preference information of the user using passwords;
a decision module 505, configured to determine, based on the benefit value, whether a password verification reminder is required for the user;
And the password verification module 507 pushes the password verification prompt to the user if the password verification prompt is needed to be carried out to the user.
The benefit module 503 further includes:
the training of the password verification model comprises the following steps:
taking the history information and the current observation value of the user as state data, wherein the history information of the user is the history information in a preset history period;
whether password verification is used or not is taken as a decision variable;
and calculating a benefit function corresponding to the state transfer function formed by the state data and the decision variables. The state transfer function is an estimate of the cryptographic verification result,
S t+1 ＝p t ＝P(a t |S t ,O t )
wherein a is t Indicating whether or not to use the password, O t S is the current observed value t For history information, p t Is the password forgetting probability.
The profit function is the profit value corresponding to the success or failure of the password verification under the current business scene, the profit value is profit or loss,
r t ＝k t *p t
wherein r is t As a benefit function, k t For risk level, p t Is the password forgetting probability.
The embodiment of the specification provides an electronic device, including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
Acquiring data to be processed, wherein the data to be processed comprises password use information and/or account value of a user and/or preference information of the user for using the password and/or password-based time information;
inputting the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method;
and if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user.
The embodiment of the present specification provides an electronic device, including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring data to be processed, wherein the data to be processed comprises a current observation value and historical information of a user;
inputting the data to be processed into a password verification model to obtain a benefit value, wherein the password verification reminding model is a model which is obtained by training in advance based on an enhanced learning method, and the current observation value comprises password forgetting probability and/or preference information of the user using a password;
Determining whether a password verification prompt is needed to be carried out on the user based on the benefit value;
if the password verification reminding needs to be carried out on the user, the password verification reminding is pushed to the user.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, electronic devices, non-volatile computer storage medium embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to the description of the method embodiments.
The apparatus, the electronic device, the nonvolatile computer storage medium and the method provided in the embodiments of the present disclosure correspond to each other, and therefore, the apparatus, the electronic device, the nonvolatile computer storage medium also have similar beneficial technical effects as those of the corresponding method, and since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, the electronic device, the nonvolatile computer storage medium are not described here again.
In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., a field programmable gate array (Field Programmable gate array, FPGA)) is an integrated circuit whose logic function is determined by the user programming the device. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.
The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing one or more embodiments of the present description.
It will be appreciated by those skilled in the art that the present description may be provided as a method, system, or computer program product. Accordingly, the present specification embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description embodiments may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present description is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the specification. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the present disclosure. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (17)
1. A password alert method comprising:
acquiring data to be processed, wherein the data to be processed comprises password use information, account value of a user, preference information of the user for using the password and password-based time information;
inputting the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model for scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method, and the password reminding model is a model obtained based on a forgetting function and related information of a user;
And if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user.
2. The method of claim 1, the method further comprising:
obtaining a benefit value by utilizing a password verification model based on a current observation value and historical information of a user, wherein the password verification model is a model which is obtained by training in advance based on an enhanced learning method, and the current observation value comprises password forgetting probability and preference information of the user for using passwords; the preference information of the user using the password comprises a service scene of the user using the password;
determining whether a password verification prompt is needed to be carried out on the user based on the benefit value;
if the password verification reminding needs to be carried out on the user, the password verification reminding is pushed to the user.
3. The method of claim 1, the data to be processed further comprising static information of the user, wherein the static information comprises an age, and/or occupation, and/or account type, and/or authentication duration, and/or on time of the user.
4. The method of claim 1, the forgetting function being a time-based function, the user-related information comprising static information of the user, and/or usage information of the password, and/or account value of the user, and/or preference information of the user for using the password, and/or password-based time information.
5. The method of claim 1, wherein the sample data of the password alert model comprises black sample tag data and white sample tag data, wherein,
the black sample tag data is data of a user who performs password resetting or password searching or losing in the password using process in the historical data;
the white sample tag data is data of a user who uses a password in the historical data and inputs the password without errors.
6. The method of claim 5, wherein the black sample tag data is data of a user performing service processing by searching a password through a port in the history data and resetting the password,
or (b)
In the history data, the data of the user lost in the process of searching the password,
or (b)
In the history data, the data of the user lost in the process of using the password is displayed.
7. The method of claim 2, the training of the password verification model comprising:
taking the history information and the current observation value of the user as state data, wherein the history information of the user is the history information in a preset history period;
whether password verification is used or not is taken as a decision variable;
and calculating a benefit function corresponding to the state transfer function formed by the state data and the decision variables.
8. The method of claim 7, wherein the state transfer function is an estimate of a cryptographic check result,
S t+1 ＝p t ＝P(a t |S t ，O t )
wherein a is t Indicating whether or not to use the password, O t S is the current observed value t For history information, p t Is the password forgetting probability.
9. The method of claim 7, wherein the benefit function is a benefit value corresponding to success or failure of password verification in the current business scenario, the benefit value is benefit or loss,
r t ＝k t *p t
wherein r is t As a benefit function, k t For risk level, p t Is the password forgetting probability.
10. A password alert method comprising:
acquiring data to be processed, wherein the data to be processed comprises a current observation value and historical information of a user, the current observation value is password forgetting probability of the user in the current transaction or the current transaction and preference information of the user using a password, and the preference information of the user using the password comprises a service scene of the user using the password;
inputting the data to be processed into a password verification model to obtain a benefit value, wherein the password verification model is a model which is obtained by training in advance based on an enhanced learning method, and the benefit value is used for reflecting the benefit of carrying out password verification reminding or not carrying out password verification reminding;
Determining whether a password verification prompt is needed to be carried out on the user based on the benefit value;
if the password verification reminding needs to be carried out on the user, the password verification reminding is pushed to the user.
11. The method of claim 10, the training of the password verification model comprising:
taking the history information and the current observation value of the user as state data, wherein the history information of the user is the history information in a preset history period;
whether password verification is used or not is taken as a decision variable;
and calculating a benefit function corresponding to the state transfer function formed by the state data and the decision variables.
12. The method of claim 11, wherein the state transfer function is an estimate of a cryptographic check result,
S t+1 ＝p t ＝P(a t |S t ，O t )
wherein a is t Indicating whether or not to use the password, O t S is the current observed value t For history information, p t Is the password forgetting probability.
13. The method of claim 11, wherein the benefit function is a benefit value corresponding to success or failure of password verification in the current business scenario, the benefit value is benefit or loss,
r t ＝k t *p t
wherein r is t As a benefit function, k t For risk level, p t Is the password forgetting probability.
14. A password alert device comprising:
The device comprises an acquisition module, a processing module and a processing module, wherein the data to be processed comprises password use information, user account value, password use preference information and password-based time information;
the scoring module inputs the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model for scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method, and the password reminding model is a model obtained based on a forgetting function and related information of a user;
and the password modification reminding module is used for pushing a password modification reminder to the user if the password forgetting probability is greater than or equal to a preset forgetting probability value.
15. A password alert device comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the data to be processed comprises a current observation value and historical information of a user, the current observation value is password forgetting probability of the user in the current transaction or the current transaction and preference information of a user using a password, and the preference information of the user using the password comprises a service scene of the user using the password;
The profit module inputs the data to be processed into a password verification model to obtain an profit value, wherein the password verification model is a model which is obtained by training in advance based on an enhanced learning method, and the profit value is used for reflecting profits of carrying out password verification reminding or not carrying out password verification reminding;
the decision module is used for determining whether the user needs to be subjected to password verification reminding based on the benefit value;
and the password verification module is used for pushing the password verification prompt to the user if the password verification prompt is needed to be carried out to the user.
16. An electronic device, comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring data to be processed, wherein the data to be processed comprises password use information, account value of a user, preference information of the user for using the password and password-based time information;
inputting the data to be processed into a password reminding model to obtain password forgetting probability corresponding to the data to be processed, wherein the password reminding model is a model for scoring the password forgetting probability, which is obtained by training in advance based on a supervised learning method, and the password reminding model is a model obtained based on a forgetting function and related information of a user;
And if the password forgetting probability is greater than or equal to a preset forgetting probability value, pushing a password modification prompt to a user.
17. An electronic device, comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring data to be processed, wherein the data to be processed comprises a current observation value and historical information of a user, the current observation value is password forgetting probability of the user in the current transaction or the current transaction and preference information of the user using a password, and the preference information of the user using the password comprises a service scene of the user using the password;
inputting the data to be processed into a password verification model to obtain a benefit value, wherein the password verification model is a model which is obtained by training in advance based on an enhanced learning method, and the benefit value is used for reflecting the benefit of carrying out password verification reminding or not carrying out password verification reminding;
determining whether a password verification prompt is needed to be carried out on the user based on the benefit value;
If the password verification reminding needs to be carried out on the user, the password verification reminding is pushed to the user.
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