WO2019109738A1 - 登录方法及装置和电子设备 - Google Patents

登录方法及装置和电子设备 Download PDF

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Publication number
WO2019109738A1
WO2019109738A1 PCT/CN2018/110671 CN2018110671W WO2019109738A1 WO 2019109738 A1 WO2019109738 A1 WO 2019109738A1 CN 2018110671 W CN2018110671 W CN 2018110671W WO 2019109738 A1 WO2019109738 A1 WO 2019109738A1
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WIPO (PCT)
Prior art keywords
brain wave
user
dynamic information
wave signal
login
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PCT/CN2018/110671
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English (en)
French (fr)
Inventor
熊务真
Original Assignee
阿里巴巴集团控股有限公司
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Publication date
Application filed by 阿里巴巴集团控股有限公司 filed Critical 阿里巴巴集团控股有限公司
Priority to SG11202000909QA priority Critical patent/SG11202000909QA/en
Priority to EP18886664.4A priority patent/EP3647976B1/en
Publication of WO2019109738A1 publication Critical patent/WO2019109738A1/zh
Priority to US16/810,619 priority patent/US11132430B2/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/36—User authentication by graphic or iconic representation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/015—Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
    • H04L63/0861—Network architectures or network communication protocols for network security for authentication of entities using biometrical features, e.g. fingerprint, retina-scan
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
    • H04L63/105—Multiple levels of security
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3226—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using a predetermined code, e.g. password, passphrase or PIN
    • H04L9/3231—Biological data, e.g. fingerprint, voice or retina
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/06—Authentication
    • H04W12/068—Authentication using credential vaults, e.g. password manager applications or one time password [OTP] applications

Definitions

  • the embodiments of the present disclosure relate to the field of Internet technologies, and in particular, to a login method and device, and an electronic device.
  • the security policy provided by the existing login method includes setting a login password.
  • the login password is at risk of being stolen.
  • a login method, device and electronic device provided by embodiments of the present specification:
  • a login method comprising:
  • the login authentication library stores a brain wave signal generated by the user for various dynamic information
  • the registration is performed.
  • a login device comprising:
  • a display unit that presents the user with dynamic information for logging in
  • Receiving unit receiving, by the monitoring device, a brain wave signal generated by the user according to the displayed dynamic information
  • the matching unit matches the monitored brain wave signal with the brain wave signal corresponding to the dynamic information in the login authentication library; wherein the login authentication library stores a brain wave signal generated by the user for various dynamic information;
  • the registration unit performs registration when the monitored electroencephalogram signal is successfully matched with the electroencephalogram signal corresponding to the dynamic information in the login authentication library.
  • an electronic device including:
  • a memory for storing processor executable instructions
  • processor is configured to:
  • the login authentication library stores a brain wave signal generated by the user for various dynamic information
  • the registration is performed.
  • the embodiment of the present specification provides a login scheme for generating brain waves based on human brain consciousness, and collects, processes, and analyzes brain wave signals generated by responding to dynamic information displayed by a user's human brain on a login device.
  • the radio signal is converted into a login command for login system docking; since the dynamic information is similar to a dynamic password, it is random and one-time; therefore, the login scheme based on human brain consciousness to generate brain waves is more conventional than the traditional login scheme. Safe, more concealed, fun, and user experience.
  • FIG. 1 is a system architecture diagram of implementing login according to an embodiment of the present disclosure
  • FIG. 2 is a schematic diagram of a monitoring device provided by an embodiment of the present specification
  • FIG. 3 is a flowchart of a login method provided by an embodiment of the present specification.
  • FIG. 4 is a schematic block diagram of a login device according to an embodiment of the present disclosure.
  • first, second, third, etc. may be used in this specification to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other.
  • first information may also be referred to as the second information without departing from the scope of the present description.
  • second information may also be referred to as the first information.
  • word "if” as used herein may be interpreted as "when” or “when” or “in response to a determination.”
  • the security policy provided by the existing login method includes setting a login password.
  • the login password here may include a traditional numeric character password or a password (such as a fingerprint, an iris, etc.) for collecting biometric information of the user.
  • the passwords thus set have a common drawback, that is, they are fixed.
  • the user's biometric information is unique and is fixed after acquisition. If the user's biometric information is leaked or obtained by someone else, the user's account is easily stolen. For example, if the user's fingerprint is collected by another person, the illegitimate person can make the fingerprint film of the user and use the fingerprint film to log in to the user account.
  • numeric character password set by the user is fixed before the user modifies it.
  • Traditional digital character passwords are more easily stolen. If a user's mobile terminal is implanted with a Trojan virus, it is easy to collect the user's login password.
  • This specification provides a scheme based on the user's brain wave real-time login, which can improve the security of user login.
  • Some basic concepts of brain waves are some basic concepts of brain waves:
  • Electroencephalogram can refer to a method of recording the activity of the human brain using electrophysiological indicators.
  • the postsynaptic potentials that occur simultaneously in a large number of neurons can form brain waves after summation.
  • Brain waves can mainly record changes in the electrical waves of human brain activity, and are an overall reflection of the electrophysiological activity of brain cells on the surface of the cerebral cortex or scalp.
  • the brain waves are derived from the postsynaptic potential of the dendrites at the apex of the pyramidal cells.
  • the formation of synchrony rhythms of brain waves is also related to the activity of the non-specific projection system of the cortical thalamus.
  • the brain waves are some spontaneous rhythmic nerve electrical activities.
  • the brain wave frequency varies generally between 1 and 30 times per second.
  • brain waves can be divided into four bands according to frequency: ⁇ (1-3 Hz), ⁇ (4-7 Hz), ⁇ (8-13 Hz), and ⁇ (14-30 Hz).
  • ⁇ 1-3 Hz
  • ⁇ 14-30 Hz
  • gamma wave with a higher frequency than the beta wave, which can be 30-80 Hz.
  • Others can have other waveforms when sleeping. Normal brain waves, such as hump waves, ⁇ waves, ⁇ waves, ⁇ -complex waves, and ⁇ waves.
  • a system architecture diagram for implementing login of the present specification may include a login device 11 and a server 12.
  • the login device 11 can be connected to the server 12 via the network 13.
  • the login device 11 can also be connected to a monitoring device (not shown in FIG. 1). Therefore, the login device 11 and the monitoring device can be connected by wire or wirelessly to transmit data.
  • the network 13 in this specification may include wired or wireless telecommunication devices through which network devices on which the login device 11 is based may exchange data.
  • each network 13 may include a local area network ("LAN”), a wide area network ("WAN”), an intranet, the Internet, a mobile telephone network, a virtual private network (VPN), a cellular or other mobile communication network, Bluetooth, NFC, or Any combination of them.
  • LAN local area network
  • WAN wide area network
  • VPN virtual private network
  • Bluetooth NFC
  • the monitoring device can be configured to monitor a brain wave signal of the user and transmit the monitored brain wave signal of the user to the login device 11.
  • the monitoring device may be provided with a brain wave wave chip, a brain wave sensor, and a data transmission device.
  • the brain wave sensor such as a dry electrode, is used to collect brain wave signals generated by the brain.
  • brainwave signals collected by brainwave sensors are usually weak, and there may be many noise signals (such as unconscious blinks, environmental influences, distractions in the user's brain, etc., which generate brainwave noise signals).
  • the brain wave chip can integrate functions such as wave filtering, amplification, A/D conversion (Analogic to Digital), data processing and analysis.
  • the filtering that is, filtering the collected brain waves, can filter out the noise signals in the brain waves and improve the anti-interference performance.
  • the A/D conversion is to convert the analog signal into a digital signal, so that the brain wave signal is quantized into a series of digital values; and then through the data processing and analysis, the complex brain wave can be decomposed into different brain state values. For example, including but not limited to attention, relaxation, brain activity, familiarity, vigilance, creativity, and the like.
  • the data transmission device is configured to transmit brain wave information processed by the brain wave chip to the registration device 11.
  • the data transmission device may comprise a wired or wireless telecommunication device on which the data transmission device on which the monitoring device is based may transmit or exchange data.
  • a wired or wireless telecommunications device may include a local area network ("LAN”), a wide area network ("WAN”), an intranet, the Internet, a mobile telephone network, a virtual private network (VPN), a cellular or other mobile communication network, Bluetooth, NFC. Or any combination thereof.
  • LAN local area network
  • WAN wide area network
  • VPN virtual private network
  • FIG. 2 Shown in Figure 2 is a schematic illustration of an exemplary monitoring device.
  • the monitoring device 141 can be a head-mounted device, and the user can perform brain wave registration by wearing such a monitoring device without using his own mobile terminal.
  • the login device 11 and the monitoring device 141 may be integrated together, and the login device 11 may include a screen 152 that may present information to a user.
  • the login device 11 may generate a login request according to the brain wave information transmitted by the monitoring device 141, and send the login request to the server 12.
  • the monitoring device shown in FIG. 2 is only an example. In practical applications, the monitoring device may be in any form as long as the monitoring of the user's brain wave signal can be realized.
  • the server 12 may refer to a server for performing login. For example, after receiving the login request sent by the login device 11, the server 12 completes the login of the user account according to the login request.
  • FIG. 3 The following describes an embodiment of a method for implementing login in the present specification, as shown in FIG. 3, which includes the following steps:
  • Step 210 Display the user with dynamic information for performing login.
  • the login device can present the user with dynamic information about the user's login.
  • the display may display dynamic information in a text or image manner through a screen of the login terminal, and the user may obtain dynamic information through visual display; or may play the dynamic information in a voice manner through a voice playback device of the login terminal, and the user obtains dynamic information through hearing.
  • the dynamic information includes one or a combination of the following:
  • the change in color can randomly generate information of multiple color changes and display it to the user; for example, blue green red, that is, the color displayed on the screen of the login terminal changes from blue to green, and then changes from green to red.
  • blue green red that is, the color displayed on the screen of the login terminal changes from blue to green, and then changes from green to red.
  • the login terminal can play the voice of the color change.
  • the brain will also react to generate brainwaves with color changes.
  • the login terminal may randomly generate a plurality of information about the length change of the blink and display it to the user, for example, the length and the length, that is, the image or the text on the screen of the login terminal that can display the blink change, blinking three times, the first blinking time is longer, the first time The second blink time is shorter, and the third blink time is longer.
  • the login terminal can play the voice of the blinking change.
  • the brain will also react to generate brain waves that change the blink of an eye.
  • the login terminal can randomly generate a plurality of information that concentrates and relaxes and displays the information to the user, for example, centralized relaxation concentration, that is, an image or a text on the screen of the login terminal that can display changes in energy, first concentrate, and then relax. Focus on it again.
  • centralized relaxation concentration that is, an image or a text on the screen of the login terminal that can display changes in energy, first concentrate, and then relax. Focus on it again.
  • the brain responds and generates brain waves with changes in energy.
  • the login terminal can play the voice with varying energy.
  • the brain will also react to generate brain waves with changes in energy.
  • the above-mentioned plurality may refer to two or more types.
  • the dynamic information including a plurality of combinations, that is, the above color change, blink change, and energy change may also be randomly combined with each other, and the combination order may also be random.
  • Step 220 Receive a brain wave signal generated by the user monitored by the monitoring device according to the displayed dynamic information.
  • the brain responds to generate brain waves of the dynamic information.
  • the monitoring device can monitor the brain wave signal generated by the user according to the displayed dynamic information; and transmit the brain wave signal to the login terminal by wire or wirelessly.
  • the brainwave wave chip in the monitoring device can quantize the brain wave signal into a series of digital values; further, through data processing and analysis, the complex brain wave can be decomposed into different brain state values, for example including but not Limited to attention, relaxation, brain activity, familiarity, vigilance, creativity, etc. In this manner, the brain wave signal received by the login terminal is the processed brain state value.
  • the monitoring device is only used to collect brain wave signals, and the brain wave wave chip may be integrated in the login terminal. In this manner, the brain wave signal received by the registration terminal is an unprocessed brain wave signal.
  • the login device also needs to process the received brain wave signal to obtain a brain state value.
  • the processing also utilizes the brain wave chip, and the processing procedure is the same as the foregoing, and will not be described again here.
  • Step 230 Match the monitored brain wave signal with the brain wave signal corresponding to the dynamic information in the login authentication library.
  • the login authentication library stores a brain wave signal generated by the user for various dynamic information.
  • the login terminal After receiving or acquiring the brain wave signal generated by the user according to the displayed dynamic information, the login terminal needs to match the brain wave signal with the brain wave signal corresponding to the dynamic information in the login authentication library.
  • the login authentication library stores a brain wave signal generated by the user that is collected in advance for various dynamic information. Usually, when users log in using brain waves for the first time, they will be prompted to collect brainwave signals generated by the brain in response to various dynamic information.
  • the login authentication can be performed based on the brain wave signal of the user who logs in the authentication library.
  • the login device can query the login authentication library to query the brainwave signals corresponding to the blue-green red pre-acquired by the user as A', B', C'.
  • A, B, and C match A', B', C'; if A and A' are the same, B and B' are the same, and C and C' are the same, the matching is successful; if not, the matching is successful. The match failed.
  • the same may include equal or similar.
  • the difference between A and A' is smaller than the threshold, it can be considered to be the same.
  • the threshold can be considered as an empirical value set in advance.
  • the brain wave signal in the login authentication library is obtained through machine learning training.
  • the machine learning module can train the pre-acquired user to brain wave information generated by various dynamic information.
  • the collected brain wave information can be modeled by using existing machine learning techniques, and by continuously iterating the optimization algorithm, the relationship between each node attribute and each node attribute can be calculated.
  • the weights are used to determine a unified equation or calculation formula; in general, such equations or calculation formulas can be referred to as models.
  • the trained brain wave model the uniqueness and accuracy of a user's brain wave characteristics can be determined, that is, the user can obtain the same calculation result for the same dynamic information in different environments.
  • the success rate of brain wave matching can be improved, and the login efficiency can be improved.
  • Step 240 When the detected brain wave signal and the brain wave signal corresponding to the dynamic information in the login authentication database are successfully matched, the registration is performed.
  • the login device can log in.
  • the performing the login may include:
  • the embodiment of the present specification provides a login scheme for generating brain waves based on human brain consciousness, and collects, processes, and analyzes brain wave signals generated by responding to dynamic information displayed by a user's human brain on a login device.
  • the radio signal is converted into a login command for login system docking; since the dynamic information is similar to a dynamic password, it is random and one-time; therefore, the login scheme based on human brain consciousness to generate brain waves is more conventional than the traditional login scheme. Safe, more concealed, fun, and user experience.
  • the step 220 may specifically include:
  • a brain wave signal generated by the user according to the displayed dynamic information and a unique identification signal of the brain wave of the user; wherein the unique identification signal of the brain wave is unique to the user Brain wave signature code;
  • the step 230 may specifically include:
  • the unique identification signals of the monitored brain waves are matched in an identity verification library; wherein the identity verification library stores unique identification signals of brain waves corresponding to different users;
  • the monitored brain wave signal is matched with a brain wave signal obtained from the login authentication library.
  • each person's brain wave signature is unique. Therefore, using the brain wave signature as the unique identification signal of the user's brain wave can well recognize the role of different users.
  • the unique identification signal of the brain wave can be referred to as brain wave ID information.
  • the identity verification library stores unique identification information of brain waves corresponding to different users collected in advance. Usually, each user will prompt and collect the unique identification information of the user's brain waves when they log in using the brain wave for the first time.
  • the login device can traverse the identity verification library after receiving the unique identification signal of the brain wave detected by the monitoring device; and if it matches the target user, obtain the login authentication database. And the brain wave signal corresponding to the dynamic information is matched by the target user; and the monitored brain wave signal generated by the user according to the displayed dynamic information is matched with the brain wave signal obtained from the login authentication library. .
  • the method further includes:
  • the step 210 specifically includes:
  • the user is presented with dynamic information for making a login.
  • the login device can monitor the current environment of the user; only in the current environment does not affect the normal generation of the brain wave. In this case, the login device can present the user with dynamic information for logging in. In this way, the authenticity of the acquired brain wave signal can be ensured, thereby improving the success rate of brain wave registration.
  • the monitoring of the current environment to determine whether the current environment affects the normal generation of brain waves specifically includes:
  • the noise decibel of the current environment does not reach the threshold, it is determined that the current environment does not affect the normal generation of brain waves.
  • the senor for monitoring the noise decibel can be set in the login device, and by monitoring the noise decibel of the current environment, it can be determined whether the pre-environment affects the normal generation of the brain wave.
  • the monitoring of the current environment to determine whether the current environment affects the normal generation of brain waves specifically includes:
  • the current ambient light intensity does not reach the threshold, it is determined that the current environment does not affect the normal generation of brain waves.
  • a sensor for monitoring the light intensity can be set in the login device, and by monitoring the illumination intensity of the current environment, it can be determined whether the front environment affects the normal generation of brain waves.
  • the factors affecting the normal generation of brain waves are not limited to the noise sum mentioned above, and may include any other factors that may affect the normal generation of brain waves in practical applications.
  • the step 210 specifically includes:
  • the user is presented with dynamic information for performing the login.
  • monitoring whether the current environment affects the normal generation of brain waves can be performed by the monitoring device.
  • the monitoring device can be provided with a sensor for monitoring the noise decibel. By monitoring the noise decibel of the current environment, it can be determined whether the pre-environment affects the normal generation of the brain wave; the monitoring device can be set for The sensor that monitors the light intensity can monitor whether the front environment affects the normal generation of brain waves by monitoring the light intensity of the current environment. For details, refer to the previous embodiment.
  • the method may further include:
  • the login is performed based on the biometric information of the user.
  • the biometric information includes, but is not limited to, at least one of a fingerprint, a palm print, an iris, an eye, a face, and a sound wave.
  • the login device may be provided with a fingerprint collector
  • the login device may be provided with a palm print collector
  • the login device may be provided with an iris collector
  • the login device may be provided with an eye pattern collector
  • the login device may set a face collector
  • the login device may be provided with a sound wave collector.
  • the biometric information can be used to challenge the brain wave authentication result. If the collected biometric information of the user matches the user himself, the login can still be performed.
  • the method further includes:
  • the collecting biometric information of the user includes:
  • the biometric information of the user is collected.
  • the threshold may be an empirical value set in advance.
  • the biometric information can be used to challenge the brain wave authentication result. If the collected biometric information of the user matches the user himself, the login can still be performed.
  • the present specification also provides an embodiment of the login device.
  • the device embodiment may be implemented by software, or may be implemented by hardware or a combination of hardware and software.
  • the processor of the device in which it is located reads the corresponding computer program instructions in the non-volatile memory into the memory.
  • a hardware structure of the device where the login device is located may include a processor, a network interface, a memory, and a non-volatile memory.
  • the device in which the device is located is generally based on the actual function of the login. Other hardware may be included and will not be described again.
  • FIG. 4 is a block diagram of a payment device according to an embodiment of the present disclosure.
  • the device corresponds to the embodiment shown in FIG. 3, and the device includes:
  • the displaying unit 310 displays the dynamic information for performing login to the user
  • the receiving unit 320 receives the brain wave signal generated by the user monitored by the monitoring device according to the displayed dynamic information
  • the matching unit 330 matches the monitored brain wave signal with the brain wave signal corresponding to the dynamic information in the login authentication library, wherein the login authentication library stores the brain wave signal generated by the user for various dynamic information. ;
  • the registration unit 340 registers the brain wave signal corresponding to the dynamic information in the registered authentication database if the detected brain wave signal is successfully matched.
  • the dynamic information includes any one or a combination of the following:
  • the brain wave signal in the login authentication library is obtained through machine learning training.
  • the receiving unit 320 specifically includes:
  • a brain wave signal generated by the user according to the displayed dynamic information and a unique identification signal of the brain wave of the user; wherein the unique identification signal of the brain wave is unique to the user Brain wave signature code;
  • the matching unit 330 specifically includes:
  • a first matching sub-unit wherein the unique identification signal of the monitored brain wave is matched in an identity verification library; wherein the identity verification library stores a unique identification signal of a brain wave corresponding to different users;
  • the second matching subunit matches the monitored brain wave signal with the brain wave signal obtained from the login authentication library.
  • the device further includes:
  • the environmental judgment sub-unit monitors the current environment to determine whether the current environment affects the normal generation of brain waves
  • the display unit 310 specifically includes:
  • the user is presented with dynamic information for logging in.
  • the environment determining subunit specifically includes:
  • noise monitoring sub-unit that monitors the noise decibel of the current environment
  • a noise judging subunit determining whether the noise decibel of the current environment reaches a threshold
  • the environment determining sub-unit determines that the current environment does not affect the normal generation of brain waves if the noise decibel of the current environment does not reach the threshold.
  • the display unit 310 specifically includes:
  • the user is presented with dynamic information for performing the login.
  • the device also includes:
  • the collecting unit collects biometric information of the user when the detected brain wave signal fails to match the brain wave signal corresponding to the dynamic information in the login authentication library;
  • the biometric registration unit registers according to the biometric information of the user.
  • the collecting unit specifically includes:
  • a statistical subunit in the case that the detected brain wave signal fails to match the brain wave signal corresponding to the dynamic information in the login authentication library, the number of times the brain wave matching fails is counted;
  • the collecting subunit collects biometric information of the user if the number of failures of the brain wave matching reaches a threshold.
  • the biometric information includes:
  • the present specification provides a registration scheme for generating brain waves based on human brain consciousness, and collecting, processing, and analyzing brain wave signals generated by responding to dynamic information displayed by a user's brain on a login device. Converting the brain wave signal into a login command for logging in to the system; since the dynamic information is similar to a dynamic password, it is random and one-time; therefore, the login scheme based on human brain consciousness generates brain waves compared to the traditional login
  • the solution is safer, more concealed, more interesting, and has a high user experience.
  • the system, device, module or unit illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product having a certain function.
  • a typical implementation device is a computer, and the specific form of the computer may be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email transceiver, and a game control.
  • the device embodiment since it basically corresponds to the method embodiment, reference may be made to the partial description of the method embodiment.
  • the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, ie may be located A place, or it can be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the objectives of the present specification. Those of ordinary skill in the art can understand and implement without any creative effort.
  • the internal function module and structure of the login device are described in FIG. 4, and the actual execution body of the device may be an electronic device, including:
  • a memory for storing processor executable instructions
  • processor is configured to:
  • the login authentication library stores a brain wave signal generated by the user for various dynamic information
  • the registration is performed.
  • the dynamic information includes any one or a combination of the following:
  • the brain wave signal in the login authentication library is obtained through machine learning training.
  • the brain wave signal generated by the user monitored according to the displayed dynamic information is monitored by the receiving monitoring device;
  • a brain wave signal generated by the user according to the displayed dynamic information and a unique identification signal of the brain wave of the user; wherein the unique identification signal of the brain wave is unique to the user Brain wave signature code;
  • the unique identification signals of the monitored brain waves are matched in an identity verification library; wherein the identity verification library stores unique identification signals of brain waves corresponding to different users;
  • the monitored brain wave signal is matched with a brain wave signal obtained from the login authentication library.
  • the method before the displaying the dynamic information for performing the login to the user, the method further includes:
  • the displaying the dynamic information for performing the login to the user includes:
  • the user is presented with dynamic information for making a login.
  • the current environment is monitored to determine whether the current environment affects the normal generation of brain waves, including:
  • the noise decibel of the current environment does not reach the threshold, it is determined that the current environment does not affect the normal generation of brain waves.
  • the displaying the dynamic information for performing the login to the user includes:
  • the user is presented with dynamic information for performing the login.
  • it also includes:
  • the login is performed based on the biometric information of the user.
  • the method before the collecting the biometric information of the user, the method further includes:
  • the collecting biometric information of the user includes:
  • the biometric information of the user is collected.
  • the biometric information includes:
  • the processor may be a central processing unit (English: Central Processing Unit, CPU for short), or other general-purpose processor, digital signal processor (English: Digital Signal Processor) , referred to as: DSP), ASIC (English: Application Specific Integrated Circuit, referred to as: ASIC).
  • the general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, and the foregoing memory may be a read-only memory (English: read-only memory, abbreviation: ROM), a random access memory (English) :random access memory (abbreviation: RAM), flash memory, hard disk or solid state disk.
  • the steps of the method disclosed in the embodiments of the present invention may be directly implemented as a hardware processor, or may be performed by a combination of hardware and software modules in the processor.

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Abstract

本说明书实施例提供一种登录方法及装置和电子设备，通过向用户展示用于进行登录的动态信息；获取监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。

Description

登录方法及装置和电子设备 技术领域
本说明书实施例涉及互联网技术领域，尤其涉及一种登录方法及装置和电子设备。
背景技术
为了保证用户账户安全，现有登录方式提供的安全策略包括设置登录密码。然而，登录密码存在被盗用的风险。
需要提供更为安全的登录方案。
发明内容
本说明书实施例提供的一种登录方法及装置和电子设备：
根据本说明书实施例的第一方面，提供一种登录方法，所述方法包括：
向用户展示用于进行登录的动态信息；
接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；
在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。
根据本说明书实施例的第二方面，提供一种登录装置，所述装置包括：
展示单元，向用户展示用于进行登录的动态信息；
接收单元，接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
匹配单元，将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信 号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；
登录单元，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。
根据本说明书实施例的第三方面，提供一种电子设备，包括：
处理器；
用于存储处理器可执行指令的存储器；
其中，所述处理器被配置为：
向用户展示用于进行登录的动态信息；
接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；
在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。
本说明书实施例，提供了一种基于人脑意识产生脑电波的登录方案，通过对用户人脑对登录设备展示的动态信息做出反应所产生的脑电波信号的采集、处理、分析，将脑电波信号转换成用于登录系统对接的登录命令；由于所述动态信息类似动态口令，是随机的、一次性的；因此，基于人脑意识产生脑电波的登录方案相比起传统的登录方案更为安全、更为隐蔽、趣味性强、用户体验高。
附图说明
图1是本说明书一实施例提供的实现登录的系统架构图；
图2是本说明书一实施例提供的监测设备的示意图；
图3是本说明书一实施例提供的登录方法的流程图；
图4是本说明书一实施例提供的登录装置的模块示意图。
具体实施方式
这里将详细地对示例性实施例进行说明，其示例表示在附图中。下面的描述涉及附图时，除非另有表示，不同附图中的相同数字表示相同或相似的要素。以下示例性实施例中所描述的实施方式并不代表与本说明书相一致的所有实施方式。相反，它们仅是与如所附权利要求书中所详述的、本说明书的一些方面相一致的装置和方法的例子。
在本说明书使用的术语是仅仅出于描述特定实施例的目的，而非旨在限制本说明书。在本说明书和所附权利要求书中所使用的单数形式的“一种”、“所述”和“该”也旨在包括多数形式，除非上下文清楚地表示其他含义。还应当理解，本文中使用的术语“和/或”是指并包含一个或多个相关联的列出项目的任何或所有可能组合。
应当理解，尽管在本说明书可能采用术语第一、第二、第三等来描述各种信息，但这些信息不应限于这些术语。这些术语仅用来将同一类型的信息彼此区分开。例如，在不脱离本说明书范围的情况下，第一信息也可以被称为第二信息，类似地，第二信息也可以被称为第一信息。取决于语境，如在此所使用的词语“如果”可以被解释成为“在……时”或“当……时”或“响应于确定”。
如前所述，为了保证用户账户安全，现有登录方式提供的安全策略包括设置登录密码。这里的登录密码可以包括传统的数字字符密码，也可以是采集用户的生物特征信息的密码(如指纹、虹膜等)。然而，上述这样设置的密码都具有一个共同的缺陷，即都是固定不变的。
一般的，用户的生物特征信息都具有唯一性，采集后是固定不变的。如果用户的生物特征信息泄露了或者被他人获取了，用户账户很容易被盗用。例如，用户指纹被他人采集，那么不法份子就可以制作该用户的指纹膜进而使用该指纹膜登录用户账户。
类似的，用户设置的数字字符密码，在用户修改前也是固定不变的。传统的数字字符密码更容易被盗用，如果用户的移动终端被植入了木马病毒，很容易就可以采集到用户的登录密码。
因此，现有的登录方式依然存在被盗用的风险。
本说明书提供了一种基于用户的脑电波现实登录的方案，可以提高用户登录的安全性。以下介绍脑电波的一些基本概念：
脑电波(Electroencephalogram，EEG)可以是指一种使用电生理指标表示人类大脑 活动的记录方式。人类大脑在活动时，大量神经元同步发生的突触后电位经总和后可以形成脑电波。脑电波主要可以记录人类大脑活动时的电波变化，是脑神经细胞的电生理活动在大脑皮层或头皮表面的总体反映。所述脑电波来源于锥体细胞顶端树突的突触后电位。脑电波同步节律的形成还与皮层丘脑非特异性投射系统的活动有关。
所述脑电波是一些自发的有节律的神经电活动。脑电波频率变动范围一般在每秒1－30次之间。通常，脑电波按频率可以划分为四个波段：δ(1－3Hz)、θ(4－7Hz)、α(8－13Hz)、β(14－30Hz)。除此之外，人类在觉醒并专注于某一事时，常可见一种频率较β波更高的γ波，其频率可以为30-80Hz；而人类在睡眠时还可出现另一些波形较为特殊的正常脑电波，如驼峰波、σ波、λ波、κ-复合波、μ波等。
本说明书可以涉及一个或多个系统。例如图1所示，本说明书的一种实现登录的系统架构图可以包括登录设备11、服务器12。所述登录设备11可以与服务器12通过网络13连接。其中，所述登录设备11还可以连接有一个监测设备(图1中未示出)。所以登录设备11与监测设备可以有线或者无线连接，从而传输数据。
本说明书中的网络13可以包括有线或无线电信装置，登录设备11所基于的网络装置可以通过所述有线或无线电信装置来交换数据。例如，每个网络13可以包括局域网(“LAN”)、广域网(“WAN”)、内部网、互联网、移动电话网络、虚拟专用网(VPN)、蜂窝式或其它移动通信网络、蓝牙、NFC或其任何组合。在示例性实施方案的讨论中，应理解，术语“数据”和“信息”可在本说明书中互换使用来指代可存在于基于计算机的环境中的文字、图像、音频、视频或任何其它形式的信息。
所述监测设备可以用于监测用户的脑电波信号，并将所监测到的用户的脑电波信号传输给所述登录设备11。具体地，所述监测设备中可以设置有包括脑电波芯片、脑电波传感器、数据传输装置。所述脑电波传感器例如干式电极，用于采集大脑产生的脑电波信号。一般的，脑电波传感器采集到的脑电波信号通常比较微弱，并且可能存在很多的噪声信号(例如无意识的眨眼，周围环境影响，用户大脑中的杂念等都会生成脑电波的噪声信号)。所述脑电波芯片可以集成脑电波信号滤波(Wave filtering)、放大、A/D转换(Analogic to Digital，模数转换)、数据处理和分析等功能。所述滤波，即对采集到的脑电波进行过滤，这样就可以过滤掉脑电波中的噪声信号，提升抗干扰性能。所述A/D转换，就是把模拟信号转换为数字信号，这样就将脑电波信号量化为一系列的数字值；进而通过数据处理和分析，可以将复杂的脑电波分解为不同的脑状态数值，例如包括但不限于关注度、放松度、脑活跃度、熟悉度、警惕度、创造力值等。所述数据传输 装置用于将脑电波芯片处理后的脑电波信息传输给登录设备11。具体地，所述数据传输装置可以包括有线或无线电信装置，所述监测设备所基于的数据传输装置可以通过所述有线或无线电信装置来传输或者交换数据。例如，有线或无线电信装置可以包括局域网(“LAN”)、广域网(“WAN”)、内部网、互联网、移动电话网络、虚拟专用网(VPN)、蜂窝式或其它移动通信网络、蓝牙、NFC或其任何组合。
图2所示的是一种示例性的监测设备的示意图。所述监测设备141可以是一种头戴式的设备，用户可以通过头戴这样监测设备就可以进行脑电波登录，而无需使用自己的移动终端。在图2中，所述登录设备11和所述监测设备141可以集成在一起，所述登录设备11可以包括有屏幕152，所述屏幕152可以向用户展示信息。所述登录设备11可以根据所述监测设备141传输的脑电波信息生成登录请求，并将所述登录请求发送给服务器12。值得一提的是，图2所示的监测设备仅是一种示例，在实际应用中，所述监测设备可以是任意形式的，只要能实现监测用户脑电波信号即可。
所述服务器12可以是指用于进行登录的服务器，例如服务器12在接收到登录设备11发送的登录请求后，根据所述登录请求完成用户账户的登录。
以下可以结合图3所示的例子介绍本说明书一种实现登录的方法的实施例，如图3所示，包括以下步骤：
步骤210：向用户展示用于进行登录的动态信息。
登录设备可以向用户展示用户进行登录的动态信息。所述展示可以通过登录终端的屏幕以文字或者图像的方式显示动态信息，用户通过视觉获取动态信息；也可以通过登录终端的语音播放装置以语音的方式播放动态信息，用户通过听觉获取动态信息。
所述动态信息包括以下一种或者多种的组合：
颜色的变化。具体地，登录终端可以随机生成多种颜色变化的信息并展示给用户；例如蓝绿红，即登录终端屏幕上显示的颜色从蓝变为绿，再从绿变为红。这样用户在看到登录终端屏幕上显示的颜色变化后，大脑就做出反应，生成蓝绿红颜色变化的脑电波。还有的，登录终端可以播放颜色变化的语音，同样地，用户在听到颜色变化的语音后，大脑也会做出反应，生成颜色变化的脑电波。
眨眼的变化。具体地，登录终端可以随机生成多种眨眼长短变化的信息并展示给用户，例如长短长，即登录终端屏幕上可以显示眨眼变化的图像或者文字，眨眼三次，第一次眨眼时间较长，第二眨眼时间较短，第三次眨眼时间较长。这样用户在看到登录终 端屏幕上显示的眨眼变化后，大脑就做出反应，生成眨眼时间长短长变化的脑电波。还有的，登录终端可以播放眨眼变化的语音，同样地，用户在听到眨眼变化的语音后，大脑也会做出反应，生成眨眼变化的脑电波。
精力的变化。具体地，登录终端可以随机生成多种精力集中、放松变化的信息并展示给用户，例如，集中放松集中，即登录终端屏幕上可以显示精力变化的图像或者文字，首先集中精力，然后放松精力，再集中精力。这样用户在看到登录终端屏幕上显示的精力变化后，大脑就做出反应，生成精力变化的脑电波。还有的，登录终端可以播放精力变化的语音，同样地，用户在听到精力变化的语音后，大脑也会做出反应，生成精力变化的脑电波。
值得一提的是，上述涉及的多种可以是指两种或者两种以上。
对于动态信息包括多种的组合，即上述颜色变化、眨眼变化、精力变化也可以随机互相组合，并且组合顺序也可以是随机的。
步骤220：接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号。
如前所述，用户在获取到登录终端展示的用于登录的动态信息之后，大脑会做出反应，生成该动态信息的脑电波。此时，监测设备就可以监测到所述用户根据所展示的动态信息产生的脑电波信号；并将该脑电波信号通过有线或无线的方式传输给登录终端。
如前所述，监测设备中的脑电波芯片可以将脑电波信号量化为一系列的数字值；进而通过数据处理和分析，可以将复杂的脑电波分解为不同的脑状态数值，例如包括但不限于关注度、放松度、脑活跃度、熟悉度、警惕度、创造力值等。这种方式中，登录终端接收到的脑电波信号即为处理后的脑状态数值。
在另一种实现方式中，所述监测设备仅用于进行脑电波信号的采集，而脑电波芯片可以是集成在登录终端的。这种方式中，登录终端接收到的脑电波信号即为未处理的脑电波信号。
进一步的，登录设备还需要对接收到的脑电波信号进行处理，从而得到脑状态数值。这里的处理同样是利用了脑电波芯片，处理过程与前述相同，此处不再赘述。
步骤230：将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号。
登录终端在接收或者获取到所述用户根据所展示的动态信息产生的脑电波信号之后，需要将所述脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配。
所述登录认证库中存储有预先采集到的用户对各种动态信息产生的脑电波信号。通常，用户在第一次使用脑电波进行登录时，会提示用户采集大脑对各种动态信息做出反应时产生的脑电波信号。
这样，以后用户再次使用脑电波进行登录时，就可以根据登录认证库中用户的脑电波信号进行登录认证了。
举例说明，假设动态信息为：蓝绿红，即登录终端屏幕上显示的颜色从蓝变为绿，再从绿变为红。采集到用户的脑电波信号假设为A，B，C(可以是指频率变化，也可以是指量化后脑状态数值的变化)。登录设备可以从登录认证库中查询该用户预先采集的蓝绿红对应的脑电波信号假设为A’，B’，C’。进而，判断A，B，C是否与A’，B’，C’匹配；如果A和A’相同，B和B’相同，C和C’相同，则说明匹配成功；如果不完全相同，则说明匹配失败。
需要说明的是，所述相同可以包括相等或者相似。例如，A和A’的差值小于阈值的情况下，也可以认为是相同。所述阈值可以认为预先设置的经验值。
在实际应用中，由于人脑的脑电波容易收到干扰，因此同一个人对同一个事物所产生的脑电波有些许差异；并且，由于脑电波较为复杂，直接匹配脑电波信号，匹配成功率低。为了解决这样问题，在本说明书提出的另一个实施例中：
所述登录认证库中的脑电波信号通过机器学习训练得到。
一般的，机器学习模块可以对预先采集到的用户对各种动态信息产生的脑电波信息进行训练。具体地，通过设置合理的函数，可以借助已有的机器学习技术对这些采集到的脑电波信息进行建模，通过不断地迭代优化算法，可以计算出各个节点属性之间的关系以及各个节点属性的权重，从而确定一个统一的方程或者计算公式；一般的，可以将这样的方程或者计算公式称之为模型。通过训练出的脑电波模型，可以确定一个用户脑电波特征的唯一性和准确性，即可以使得用户在不同环境中对于相同的动态信息可以得到相同的计算结果。通过机器学习技术，可以提高脑电波匹配的成功率，进而可以提高登录效率。
步骤240：在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。
在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，登录设备可以进行登录。
具体地，所述进行登录，可以包括：
生成所述用户的登录请求，并将所述登录请求发送给服务器。
本说明书实施例，提供了一种基于人脑意识产生脑电波的登录方案，通过对用户人脑对登录设备展示的动态信息做出反应所产生的脑电波信号的采集、处理、分析，将脑电波信号转换成用于登录系统对接的登录命令；由于所述动态信息类似动态口令，是随机的、一次性的；因此，基于人脑意识产生脑电波的登录方案相比起传统的登录方案更为安全、更为隐蔽、趣味性强、用户体验高。
在本说明书的一个具体地实施例中，所述步骤220，具体可以包括：
接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号和所述用户的脑电波的唯一标识信号；其中，所述脑电波的唯一标识信号为用户特有的具有唯一性的脑电波特征码；
所述步骤230，具体可以包括：
将所述监测到的脑电波的唯一标识信号在身份验证库进行匹配；其中，所述身份验证库中存储有不同用户对应的脑电波的唯一标识信号；
在匹配到目标用户的情况下，获取登录认证库中所述目标用户对于该动态信息对应的脑电波信号；
将所述监测到的脑电波信号与从所述登录认证库中获取到的脑电波信号进行匹配。
本实施例中，每个人的脑电波特征码都是唯一的。因此，利用脑电波特征码作为用户脑电波的唯一标识信号，可以很好的起到识别不同用户的作用。一般的，可以将脑电波的唯一标识信号称之为脑电波ID信息。
与登录认证库类似的，身份验证库中存储有预先采集到的不同用户对应的脑电波的唯一标识信息。通常，每一个用户在第一次使用脑电波进行登录时，都会提示并采集用户脑电波的唯一标识信息。
如此，在用户进行脑电波登录过程中，登录设备在接收到监测设备监测到的脑电波的唯一标识信号后，可以遍历身份验证库；在匹配到目标用户的情况下，获取登录认证库中所述目标用户对于该动态信息对应的脑电波信号；进而将所述监测到的所述用户根 据所展示的动态信息产生的脑电波信号与从所述登录认证库中获取到的脑电波信号进行匹配。
通过本实施例，可以进一步提升登录安全性。
在本说明书的一个具体地实施例中，
在所述步骤210之前，所述方法还包括：
对当前环境进行监测，判断当前环境是否影响脑电波的正常生成；
所述步骤210，具体包括：
在当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
本实施例中，由于人脑的脑电波信号容易受到周围环境的影响；因此进行脑电波登录之前，登录设备可以对用户的当前环境进行监测；只有在在当前环境不影响脑电波的正常生成的情况下，登录设备就可以向用户展示用于进行登录的动态信息。这样，就可以保证采集到的脑电波信号的真实性，从而提升脑电波登录的成功率。
在一种实现方式中，所述对当前环境进行监测，判断当前环境是否影响脑电波的正常生成，具体包括：
监测当前环境的噪声分贝；
判断当前环境的噪声分贝是否达到阈值；
在当前环境的噪声分贝未达到阈值的情况下，确定当前环境不影响脑电波的正常生成。
通常，环境的噪声是影响脑电波正常生成的一个重要因素。因此，可以在登录设备中设置用于监测噪声分贝的传感器，通过对当前环境的噪声分贝的监测，可以判断前环境是否影响脑电波的正常生成。
在另一种实现方式中，所述对当前环境进行监测，判断当前环境是否影响脑电波的正常生成，具体包括：
监测当前环境的光照强度；
判断当前环境的光照强度是否达到阈值；
在当前环境的光照强度未达到阈值的情况下，确定当前环境不影响脑电波的正常生 成。
通常，环境的光照强度是影响脑电波正常生成的一个重要因素。因此，可以在登录设备中设置用于监测光照强度的传感器，通过对当前环境的光照强度的监测，可以判断前环境是否影响脑电波的正常生成。
需要说明的是，影响脑电波正常生成的因素不限上述的噪声和，在实际应用中可以包括其它可能影响脑电波正常生成的任意因素。
在本说明书的一个具体地实施例中，
所述步骤210，具体包括：
在接收到监测设备发送的当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
本实施例与上一实施例不同之处在于，监测当前环境是否影响脑电波的正常生成可以是由监测设备完成的。与上一实施例类似的，监测设备中可以设置用于监测噪声分贝的传感器，通过对当前环境的噪声分贝的监测，可以判断前环境是否影响脑电波的正常生成；监测设备中可以设置用于监测光照强度的传感器，通过对当前环境的光照强度的监测，可以判断前环境是否影响脑电波的正常生成。具体可以参考上一实施例。
在本说明书的一个具体地实施例中，
基于图3所示实施例，在步骤230之后，还可以包括：
在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败的情况下，采集用户的生物特征信息；
根据所述用户的生物特征信息进行登录。
本实施例中，所述生物特征信息包括但不限于：指纹、掌纹、虹膜、眼纹、人脸、声波中的至少一种。
为了实现采集用户的指纹，所述登录设备可以设置有指纹采集器；
为了实现采集用户的掌纹，所述登录设备可以设置有掌纹采集器；
为了实现采集用户的虹膜，所述登录设备可以设置有虹膜采集器；
为了实现采集用户的眼纹，所述登录设备可以设置有眼纹采集器；
为了实现采集用户的人脸，所述登录设备可以设置有人脸采集器；
为了实现采集用户的声波，所述登录设备可以设置有声波采集器。
通过本实施例，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败的情况下，可以利用生物特征信息对脑电波认证结果进行挑战。如果采集到的用户的生物特征信息符合用户本人，则依然可以进行登录。
在本说明书的一个具体地实施例中，
在所述采集用户的生物特征信息之前，所述方法还包括：
统计脑电波匹配失败的次数；
所述采集用户的生物特征信息，具体包括：
在所述脑电波匹配失败的次数到达阈值的情况下，采集用户的生物特征信息。
本实施例中，所述阈值可以是预先设置的一个经验值。通过本实施例，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败次数到达阈值的情况下，可以利用生物特征信息对脑电波认证结果进行挑战。如果采集到的用户的生物特征信息符合用户本人，则依然可以进行登录。
与前述登录方法实施例相对应，本说明书还提供了登录装置的实施例。所述装置实施例可以通过软件实现，也可以通过硬件或者软硬件结合的方式实现。以软件实现为例，作为一个逻辑意义上的装置，是通过其所在设备的处理器将非易失性存储器中对应的计算机程序指令读取到内存中运行形成的。从硬件层面而言，本说明书登录装置所在设备的一种硬件结构可以包括处理器、网络接口、内存以及非易失性存储器之外，实施例中装置所在的设备通常根据该登录实际功能，还可以包括其他硬件，对此不再赘述。
参见图4，为本说明书一实施例提供的支付装置的模块图，所述装置对应了图3所示实施例，所述装置包括：
展示单元310，向用户展示用于进行登录的动态信息；
接收单元320，接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
匹配单元330，将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；
登录单元340，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑 电波信号匹配成功的情况下，进行登录。
在一个可选的实施例中：
所述动态信息包括以下任意一种或者多种的组合：
颜色的变化；
眨眼的变化；
精力的变化。
在一个可选的实施例中：
所述登录认证库中的脑电波信号通过机器学习训练得到。
在一个可选的实施例中：
所述接收单元320，具体包括：
接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号和所述用户的脑电波的唯一标识信号；其中，所述脑电波的唯一标识信号为用户特有的具有唯一性的脑电波特征码；
所述匹配单元330，具体包括：
第一匹配子单元，将所述监测到的脑电波的唯一标识信号在身份验证库进行匹配；其中，所述身份验证库中存储有不同用户对应的脑电波的唯一标识信号；
获取子单元，在匹配到目标用户的情况下，获取登录认证库中所述目标用户对于该动态信息对应的脑电波信号；
第二匹配子单元，将所述监测到的脑电波信号与从所述登录认证库中获取到的脑电波信号进行匹配。
在一个可选的实施例中：
在所述展示单元310之前，所述装置还包括：
环境判断子单元，对当前环境进行监测，判断当前环境是否影响脑电波的正常生成；
所述展示单元310，具体包括：
在当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动 态信息。
在一个可选的实施例中：
所述环境判断子单元，具体包括：
噪声监测子单元，监测当前环境的噪声分贝；
噪声判断子单元，判断当前环境的噪声分贝是否达到阈值；
环境确定子单元，在当前环境的噪声分贝未达到阈值的情况下，确定当前环境不影响脑电波的正常生成。
在一个可选的实施例中：
所述展示单元310，具体包括：
在接收到监测设备发送的当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
在一个可选的实施例中：
所述装置还包括：
采集单元，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败的情况下，采集用户的生物特征信息；
生物登录单元，根据所述用户的生物特征信息进行登录。
在一个可选的实施例中：
所述采集单元，具体包括：
统计子单元，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败的情况下，统计脑电波匹配失败的次数；
采集子单元，在所述脑电波匹配失败的次数到达阈值的情况下，采集用户的生物特征信息。
在一个可选的实施例中：
所述生物特征信息包括：
指纹、掌纹、虹膜、眼纹、人脸、声波中的至少一种。
综上所述，本说明书提供了一种基于人脑意识产生脑电波的登录方案，通过对 用户人脑对登录设备展示的动态信息做出反应所产生的脑电波信号的采集、处理、分析，将脑电波信号转换成用于登录系统对接的登录命令；由于所述动态信息类似动态口令，是随机的、一次性的；因此，基于人脑意识产生脑电波的登录方案相比起传统的登录方案更为安全、更为隐蔽、趣味性强、用户体验高。
上述实施例阐明的系统、装置、模块或单元，具体可以由计算机芯片或实体实现，或者由具有某种功能的产品来实现。一种典型的实现设备为计算机，计算机的具体形式可以是个人计算机、膝上型计算机、蜂窝电话、相机电话、智能电话、个人数字助理、媒体播放器、导航设备、电子邮件收发设备、游戏控制台、平板计算机、可穿戴设备或者这些设备中的任意几种设备的组合。
上述装置中各个单元的功能和作用的实现过程具体详见上述方法中对应步骤的实现过程，在此不再赘述。
对于装置实施例而言，由于其基本对应于方法实施例，所以相关之处参见方法实施例的部分说明即可。以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本说明书方案的目的。本领域普通技术人员在不付出创造性劳动的情况下，即可以理解并实施。
以上图4描述了登录装置的内部功能模块和结构示意，其实质上的执行主体可以为一种电子设备，包括：
处理器；
用于存储处理器可执行指令的存储器；
其中，所述处理器被配置为：
向用户展示用于进行登录的动态信息；
接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；
在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。
可选的，所述动态信息包括以下任意一种或者多种的组合：
颜色的变化；
眨眼的变化；
精力的变化。
可选的，所述登录认证库中的脑电波信号通过机器学习训练得到。
可选的，所述接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号和所述用户的脑电波的唯一标识信号；其中，所述脑电波的唯一标识信号为用户特有的具有唯一性的脑电波特征码；
所述将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配，具体包括：
将所述监测到的脑电波的唯一标识信号在身份验证库进行匹配；其中，所述身份验证库中存储有不同用户对应的脑电波的唯一标识信号；
在匹配到目标用户的情况下，获取登录认证库中所述目标用户对于该动态信息对应的脑电波信号；
将所述监测到的脑电波信号与从所述登录认证库中获取到的脑电波信号进行匹配。
可选的，在所述向用户展示用于进行登录的动态信息之前，还包括：
对当前环境进行监测，判断当前环境是否影响脑电波的正常生成；
所述向用户展示用于进行登录的动态信息，具体包括：
在当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
可选的，所述对当前环境进行监测，判断当前环境是否影响脑电波的正常生成，具体包括：
监测当前环境的噪声分贝；
判断当前环境的噪声分贝是否达到阈值；
在当前环境的噪声分贝未达到阈值的情况下，确定当前环境不影响脑电波的正常生成。
可选的，所述向用户展示用于进行登录的动态信息，具体包括：
在接收到监测设备发送的当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
可选的，还包括：
在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败的情况下，采集用户的生物特征信息；
根据所述用户的生物特征信息进行登录。
可选的，在所述采集用户的生物特征信息之前，还包括：
统计脑电波匹配失败的次数；
所述采集用户的生物特征信息，具体包括：
在所述脑电波匹配失败的次数到达阈值的情况下，采集用户的生物特征信息。
可选的，所述生物特征信息包括：
指纹、掌纹、虹膜、眼纹、人脸、声波中的至少一种。
在上述电子设备的实施例中，应理解，该处理器可以是中央处理单元(英文：Central Processing Unit，简称：CPU)，还可以是其他通用处理器、数字信号处理器(英文：Digital Signal Processor，简称：DSP)、专用集成电路(英文：Application Specific Integrated Circuit，简称：ASIC)等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等，而前述的存储器可以是只读存储器(英文：read-only memory，缩写：ROM)、随机存取存储器(英文：random access memory，简称：RAM)、快闪存储器、硬盘或者固态硬盘。结合本发明实施例所公开的方法的步骤可以直接体现为硬件处理器执行完成，或者用处理器中的硬件及软件模块组合执行完成。
本说明书中的各个实施例均采用递进的方式描述，各个实施例之间相同相似的部分互相参见即可，每个实施例重点说明的都是与其他实施例的不同之处。尤其，对于电子设备实施例而言，由于其基本相似于方法实施例，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。
本领域技术人员在考虑说明书及实践这里公开的发明后，将容易想到本说明书的其它实施方案。本说明书旨在涵盖本说明书的任何变型、用途或者适应性变化，这些变型、用途或者适应性变化遵循本说明书的一般性原理并包括本说明书未公开的本技术领域中的公知常识或惯用技术手段。说明书和实施例仅被视为示例性的，本说明书的真正范围和精神由下面的权利要求指出。
应当理解的是，本说明书并不局限于上面已经描述并在附图中示出的精确结构，并且可以在不脱离其范围进行各种修改和改变。本说明书的范围仅由所附的权利要求来限制。

Claims (21)

  1. 一种登录方法，所述方法包括：
    向用户展示用于进行登录的动态信息；
    接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
    将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；
    在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。
  2. 根据权利要求1所述的方法，所述动态信息包括以下任意一种或者多种的组合：
    颜色的变化；
    眨眼的变化；
    精力的变化。
  3. 根据权利要求1所述的方法，所述登录认证库中的脑电波信号通过机器学习训练得到。
  4. 根据权利要求1所述的方法，所述接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
    接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号和所述用户的脑电波的唯一标识信号；其中，所述脑电波的唯一标识信号为用户特有的具有唯一性的脑电波特征码；
    所述将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配，具体包括：
    将所述监测到的脑电波的唯一标识信号在身份验证库进行匹配；其中，所述身份验证库中存储有不同用户对应的脑电波的唯一标识信号；
    在匹配到目标用户的情况下，获取登录认证库中所述目标用户对于该动态信息对应的脑电波信号；
    将所述监测到的脑电波信号与从所述登录认证库中获取到的脑电波信号进行匹配。
  5. 根据权利要求1所述的方法，在所述向用户展示用于进行登录的动态信息之前，所述方法还包括：
    对当前环境进行监测，判断当前环境是否影响脑电波的正常生成；
    所述向用户展示用于进行登录的动态信息，具体包括：
    在当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
  6. 根据权利要求5所述的方法，所述对当前环境进行监测，判断当前环境是否影响脑电波的正常生成，具体包括：
    监测当前环境的噪声分贝；
    判断当前环境的噪声分贝是否达到阈值；
    在当前环境的噪声分贝未达到阈值的情况下，确定当前环境不影响脑电波的正常生成。
  7. 根据权利要求1所述的方法，所述向用户展示用于进行登录的动态信息，具体包括：
    在接收到监测设备发送的当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
  8. 根据权利要求1所述的方法，所述方法还包括：
    在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败的情况下，采集用户的生物特征信息；
    根据所述用户的生物特征信息进行登录。
  9. 根据权利要求8所述的方法，在所述采集用户的生物特征信息之前，所述方法还包括：
    统计脑电波匹配失败的次数；
    所述采集用户的生物特征信息，具体包括：
    在所述脑电波匹配失败的次数到达阈值的情况下，采集用户的生物特征信息。
  10. 根据权利要求8或9所述的方法，所述生物特征信息包括：
    指纹、掌纹、虹膜、眼纹、人脸、声波中的至少一种。
  11. 一种登录装置，应该于登录设备，所述装置包括：
    展示单元，向用户展示用于进行登录的动态信息；
    接收单元，接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
    匹配单元，将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；
    登录单元，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。
  12. 根据权利要求11所述的装置，所述动态信息包括以下任意一种或者多种的组合：
    颜色的变化；
    眨眼的变化；
    精力的变化。
  13. 根据权利要求11所述的装置，所述登录认证库中的脑电波信号通过机器学习训练得到。
  14. 根据权利要求11所述的装置，所述接收单元，具体包括：
    接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号和所述用户的脑电波的唯一标识信号；其中，所述脑电波的唯一标识信号为用户特有的具有唯一性的脑电波特征码；
    所述匹配单元，具体包括：
    第一匹配子单元，将所述监测到的脑电波的唯一标识信号在身份验证库进行匹配；其中，所述身份验证库中存储有不同用户对应的脑电波的唯一标识信号；
    获取子单元，在匹配到目标用户的情况下，获取登录认证库中所述目标用户对于该动态信息对应的脑电波信号；
    第二匹配子单元，将所述监测到的脑电波信号与从所述登录认证库中获取到的脑电波信号进行匹配。
  15. 根据权利要求11所述的装置，在所述展示单元之前，所述装置还包括：
    环境判断子单元，对当前环境进行监测，判断当前环境是否影响脑电波的正常生成；
    所述展示单元，具体包括：
    在当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
  16. 根据权利要求15所述的装置，所述环境判断子单元，具体包括：
    噪声监测子单元，监测当前环境的噪声分贝；
    噪声判断子单元，判断当前环境的噪声分贝是否达到阈值；
    环境确定子单元，在当前环境的噪声分贝未达到阈值的情况下，确定当前环境不影响脑电波的正常生成。
  17. 根据权利要求11所述的装置，所述展示单元，具体包括：
    在接收到监测设备发送的当前环境不影响脑电波的正常生成的情况下，向用户展示用于进行登录的动态信息。
  18. 根据权利要求11所述的装置，所述装置还包括：
    采集单元，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败的情况下，采集用户的生物特征信息；
    生物登录单元，根据所述用户的生物特征信息进行登录。
  19. 根据权利要求18所述的装置，所述采集单元，具体包括：
    统计子单元，在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配失败的情况下，统计脑电波匹配失败的次数；
    采集子单元，在所述脑电波匹配失败的次数到达阈值的情况下，采集用户的生物特征信息。
  20. 根据权利要求18或19所述的装置，所述生物特征信息包括：
    指纹、掌纹、虹膜、眼纹、人脸、声波中的至少一种。
  21. 一种电子设备，包括：
    处理器；
    用于存储处理器可执行指令的存储器；
    其中，所述处理器被配置为：
    向用户展示用于进行登录的动态信息；
    接收监测设备监测到的所述用户根据所展示的动态信息产生的脑电波信号；
    将所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号进行匹配；其中，所述登录认证库中存储有用户对各种动态信息产生的脑电波信号；
    在所述监测到的脑电波信号与登录认证库中该动态信息对应的脑电波信号匹配成功的情况下，进行登录。
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