Biometrics are increasingly used to provide authentication and/or verification of a user in many security and financial applications for example. However, “spoof attacks” through presentation of biometric artefacts that are “false” allow attackers to fool these biometric verification systems. Accordingly, it would be beneficial to further differentiate the acquired biometric characteristics into feature spaces relating to live and non-living biometrics to prevent non-living biometric credentials triggering biometric verification. The inventors have established a variety of “liveness” detection methodologies which can block either low complexity spoofs or more advanced spoofs. Such techniques may provide for monitoring of responses to challenges discretely or in combination with additional aspects such as the timing of user's responses, depth detection within acquired images, comparison of other images from other cameras with database data etc.

Implementations are directed to enabling a representative associated with an entity to quickly and efficiently modify a voice bot associated with the entity. The voice bot can be previously trained to communicate with user(s) on behalf of the entity through various communication channels (e.g., a telephone communication channel, a software application communication channel, a messaging communication channel, etc.). Processor(s) of a computing device can receive, from the representative, representative input to modify behavior(s) and/or parameter(s) that the voice bot utilizes in communicating with the plurality of users via the communication channels, determine whether the representative is authorized to cause the behavior(s) and/or parameter(s) to be modified, and cause the behavior(s) and/or parameter(s) to be modified in response to determining that the representative is authorized. Notably, the representative input can be received through the same communication channels that the user(s) utilize to communicate with the voice bot.

Systems and methods are disclosed for identifying human users on a network. One method includes receiving network data comprising data transmitted over a network over predetermined time period, the network data comprising a plurality of usernames and a plurality of events, wherein each of the plurality of events is associated with at least one of the plurality of usernames; determining a plurality of pairs, each pair of the plurality of pairs comprising a username of the plurality of usernames and an associated event of the plurality of events; determining qualifying pairs of the plurality of pairs, the qualifying pairs corresponding to a subset of the plurality of pairs that meet or exceed one or more predetermined event frequency thresholds; determining non-qualifying pairs of the plurality of pairs, the non-qualifying pairs corresponding to the subset of the plurality of pairs that do not meet or exceed one or more predetermined event frequency thresholds; generating at least one distribution associated with the qualifying pairs and non-qualifying pairs; and based on the at least one distribution, determining if at least one username of the plurality of usernames is associated with a human user or a non-human user.

A system and method for scheduling tasks associated with changing a personality of a ticketing interface. One or more processors generate interaction scores for each of the plurality of user devices based on receiving interactions between the ticketing engine and a plurality of user devices. The system further generate interaction patterns for each of the plurality of user devices that include a relation between the interaction scores generated for each of the plurality of user devices with the interactions from the plurality of user devices. The system further classify each of the plurality of user devices based on the generated interaction patterns to identify whether a user device from the plurality of user devices is a fraudulent or a non-fraudulent user device and modify interface of the ticketing engine based on the classification of each of the plurality of user devices.

A charger for an electronic nicotine delivery systems (“ENDS”) device, which may include aerosol delivery devices provides functionality for authentication, including age verification. Such devices may be restricted based on age or other factors that require some form of authentication, verification, and/or identification to satisfy the restriction. The accessory or charger may provide or connect with a verification system for confirming an age of a user. If the authentication or verification is not satisfied, the charger or accessory will not charge the device, rendering it unusable.

An email address is provided by a user when the user registers an account with a service provider. A unique ID is generated for the user. An email containing the unique ID is sent to the email address. The unique ID is embedded as a part of a URL link or in a loadable image. A user response to the email is detected. The user response includes a request to access the URL link or to load the image. Subsequently, the unique ID is retrieved from the request. The email address is confirmed as a valid email address if the retrieved unique ID is identical to the generated unique ID. A Turing test is conducted to determine whether the user is a computer bot. Access to the user account is granted only if the email address is confirmed as valid and the user is determined to not be a bot.

Acoustic signatures can be used in connection with a voice-enabled computer system. An acoustic signature can be a specific noise pattern (or other sound) that is played while the user is speaking and that is mixed in the acoustic channel with the user's speech. The microphone of the voice-enabled computer system can capture, as recorded audio, a mix of the acoustic signature and the user's voice. The voice-enabled computer system can analyze the recorded audio (locally or at a backend server) to verify that the expected acoustic signature is present and/or that no previous acoustic signature is present.

An apparatus verifies hosted information associated with a user. The apparatus establishes, by the online host serving as a relying party system (RPS), a secure connection between the RPS and a user mobile-identification-credential device (UMD). The RPS sends a mobile identification credential (MIC) user information request to the UMD, via the secure connection, seeking release of MIC user information (official information). The RPS obtains from authorizing party system (APS) verification of the MIC user information received in response to the MIC user information request. The RPS stores the MIC user information as hosted information pertaining to the user. The RPS designates the hosted information as base truth information representing the user.

A method to recognize whether a user of an electronic terminal is a human or a robot is described. This method provides to take an image and decompose the image in a multitude of image portions. The image portions are randomly visualized inside a test area of an electronic terminal. The method provides to detect the movement of a cursor inside the test area, and to move each image portion inside the test area according to a trajectory which depends on the position of the cursor inside the test area. When the cursor is in a solution position inside the test area, the image portions combine into the original image. The coordinates of the solution position are randomly generated, and to these coordinates is associated a solution area which comprises the coordinates of the solution position. In order to recognize if a user of an electronic terminal is a human or a robot, the method tests if the cursor position is inside the solution area when the user inputs a control signal.

A dyschromatopsia deciding method and apparatus is provided. The apparatus includes an I/O interface configured to receive an input for a program, a memory configured to store the input for the program and a processing result of the input, and a processor configured to execute the program, wherein the processor is configured to provide first CAPTCHA information for distinguishing between a person and a machine together with second CAPTCHA information for deciding dyschromatopsia, receive first CAPTCHA input information corresponding to the first CAPTCHA information and second CAPTCHA input information corresponding to the second CAPTCHA information together with authentication information, authenticate a user based on the first CAPTCHA input information, decide dyschromatopsia of the user based on the second CAPTCHA input information, and store a decision result of the dyschromatopsia in response to a decision that the user has the dyschromatopsia.