Abstract: Disclosed herein are system, method, and computer program product embodiments for protecting user data privacy in a privacy zone around a user and a computing device displaying user data. A device can include a camera configured to capture a sequence of images in a location, such as in a privacy zone comprising an area around the device and a user of the device. A memory can be coupled to the camera to store the sequence of images. A monitoring device can be configured to determine, based on the sequence of images, whether an object is found in the location. In response to finding an object, the monitoring device can generate a control signal to cause the device to take an action to protect the user data privacy in the location such as a privacy zone.

Abstract: Systems and method for providing information about a location with image analysis are described herein. The method can include: retrieving, from a user's device, location information, receiving a digital image of an location captured by a digital camera connected to the user's device, analyzing the digital image to detect an identification feature, determining an identify of the location based on the location information and the identification feature, identifying a capture time of day at which the digital image was captured, determining a median rate of traffic at the establish at the identified capture time of day, calculating information based on the median rate of traffic at the capture time of day, the information related to how crowded the location is at the captured time of day, and providing, by a display on the user's device, the information.

Abstract: A device receives, from a user device, a request to generate a verification code for a transaction associated with a user of the user device, and receives user profile information associated with a transaction card to be used for the transaction. The device generates a random verification code for the transaction based on the request and the user profile information, and authenticates the random verification code, based on the user profile information, to generate an authenticated random verification code. The device provides the authenticated random verification code to the user device, and receives transaction information, including the authenticated random verification code, from a merchant device associated with the transaction. The device validates the transaction based on the transaction information, and provides, to the merchant device associated with the transaction, information indicating that the transaction is validated.

Abstract: Systems and methods of provisioning post-interaction values are disclosed.

Abstract: The innovation disclosed, in one aspect thereof, comprises systems and methods of a browser extension for product quality. Online shopping by a user can be monitored on a browser by a browser extension or integrated application with the browser. A potential purchase of a product is detected by the integrated application. The product is identified via analysis of a web page and cross reference to known products. The integrated application retrieves warranty claims data from an accessible warranty database. The warranty claims data is analyzed to determine a recommendation of the product. The integrated application presents the recommendation via the browser as an alert to the user.

Abstract: Methods, systems, and apparatuses are described herein for improving computer authentication processes through computer-based authentication in a manner that uses knowledge of former devices. A computing device may train a machine learning model to output an indication of device reliability data associated with a particular device. The computing device may receive a request for access to an account from a user. The computing device may receive account data and provide the account data to the trained machine learning model. The computing device may receive data indicating device reliability for a set of devices from the machine learning model. The computing device may generate a modified set of device choices for the user by excluding devices having reliability levels below a threshold value. An authentication question may be generated, and access to the account may be provided based on a response to the authentication question.

Abstract: Disclosed are methods and systems for generating a virtual tag for an item in a physical environment. For instance, an image of the physical environment captured by and displayed on a user interface of a computing device may be provided as input to a trained machine learning model configured to identify the item including a first subset of item attributes. The item may be identified and information associated with the item, including a second subset of item attributes, may be received from a data store using the first subset. A spatial location of the item may be identified in the image. An icon may be generated for the item and rendered by the computing device for display on the user interface in association with the spatial location of the item in the image. The icon may be indicative of at least one item attribute from the first or second subset.

Abstract: Methods and systems for generating electronic signatures are disclosed. In some embodiments, the method includes: storing pixel features of a signing device; capturing, via an imaging device, a plurality of image frames including the pixel features of the signing device; identifying in the plurality of image frames, by a processor, first pixels matching the stored pixel features of the signing device; generating, by the processor, a first image including the identified pixels; and connecting, by the processor, the identified pixels to form at least one line drawing representing a signature.

Abstract: The disclosed systems and methods may request a merchant identifier associated with a merchant from a third party, receive the merchant identifier, retrieve or receive a first uniform resource locator (URL) associated with the merchant, and store the merchant identifier and the first URL in a database. In response to a web browser extension detecting that a user is preparing to make an online purchase associated with the merchant, the system may receive an age request for an age of the merchant from a user device and identify the merchant identifier in the database based on a second URL included in the age request. The system may then request the age of the merchant from the database based on the merchant identifier, receive the age of the merchant from the third party, and transmit the age of the merchant to the user device for display.

Abstract: Systems and methods for fraud detection and prevention is disclosed. The system may receive a transaction request for a first customer including a transaction location, transaction time stamp, and merchant type code. The system may determine whether the transaction location is expected for the first customer. When the transaction location is unexpected, the system may identify a last-known video detection having a last-known time stamp and last-known location. The system may determine a travel time estimate between the last-known location and the transaction location and determine a buffer based on the merchant type code. The system may compare the travel time estimate to an allotted time that includes a difference between the transaction time stamp and last-known time stamp less the buffer. When the travel time estimate exceeds the allotted time, the system may execute one or more fraud prevention steps.

Abstract: In some implementations, a device may receive, from a terminal, an indication of a first card credential associated with a card that was provided to the terminal to initiate a first interaction, where the card is associated with the multiple card credentials, including the first card credential. The device may determine that the first card credential is valid based on at least one of: the first card credential having not been previously used for another interaction associated with the card, or a first amount of time, from a first time indicated by a first timestamp associated with the first card credential to a reception time of the first card credential, satisfying a validity threshold. The device may transmit, to the terminal, an indication that the card is approved for the first interaction based on the first card credential being determined to be valid.

Abstract: An automated teller machine (ATM) may include an input component and one or more processors. The input component may be configured to detect multi-factor input associated with an account. The multi-factor input may include at least two of: a sequence of characters input via the input component, a force with which at least one character, of the sequence of characters, is input via the input component, a length of time over which at least one character, of the sequence of characters, is input via the input component, or a combination of at least two characters, of the sequence of characters, that are input concurrently via the input component. The ATM may receive the multi-factor input, validate the multi-factor input in association with the account, and selectively permit or deny access to one or more actions associated with the account based on validating the multi-factor input.

Abstract: A method for generating virtual certification number data may comprise: receiving real-time image data from a camera of a user device; parsing location features data from the real-time image data; determining, based on the location features data, a location of the user device; upon determining the location of the user device, detecting, based on the real-time image data, a terminal at the location; upon detecting the terminal at the location, generating virtual certification number data for the user specific to the location; causing the user device to store the virtual certification number data for the user on a memory device associated with the user device; and transmitting the virtual certification number data to the terminal at the location.

Abstract: A software module, executed locally on a user device, may monitor a plurality of user interactions with one or more interfaces. The plurality of user interactions may be exclusive of item level data of the one or more interfaces. The plurality of user interactions may be provided to a machine-learning model. The machine-learning model may have been trained to identify user interest behavior patterns and output a user interest score. The machine-learning model may output the user interest score based on the plurality of user interactions. It may be determined that the user interest score exceeds a user interest score threshold. A capturing of the item level data of the one or more interfaces may be triggered based on the user interest score exceeding the user interest score threshold. The item level data of the one or more interfaces may be stored locally on the user device.

Abstract: A computer-implemented method for providing presentable transaction data of a product to a user may include obtaining preliminary transaction data of one or more purchasers other than the user; generating itemized transaction data based on the preliminary transaction data; obtaining one or more translation codes from one or more transaction entities; generating standardized transaction data based on the itemized transaction data and the one or more translation codes; retrieving identification data from the standardized transaction data; generating anonymized transaction data based on the standardized transaction data by withholding the identification data; generating presentable transaction data based on the anonymized transaction data; and transmitting, to a device associated with the user, the presentable transaction data.

Abstract: A computer-implemented method of fraud protection is described. A server may receive one or more keywords and a likelihood of fraud from an external source. The server may receive an image of a document from a user device, wherein the document comprises at least one of a written communication or a printed communication. The server may extract text from the image of the document, compare the extracted text to the one or more stored keywords, and calculate a confidence level of fraud. The server may send an indication of the confidence level of fraud to the user device.

Abstract: Systems and methods of the present disclosure include computer systems for improving data security. To do so, an authorization request associated with a user profile is received, including a time-stamp for a profile activity, a profile identifier, and a value. Application analytics data for a software application on a user device associated with the user profile is accessed, including an open event indicator indicating a time of a loading, and a close event indicator indicating a time of a termination. An open period of the software application at the time-stamp is determined based on the application open event indicator and the application close event indicator. A reduced set of fraud checks is selected and executed when the time-stamp associated with the profile activity is within the open period of the software application. A fraud determination is generated, and an authorization notification is generated based on the fraud determination.

Abstract: Methods and systems are described herein for identifying malicious activity using deep-linked items related to stochastic images. The system may receive event data associated with an event performed in connection with a token. The system may generate a token embedding based on the event data and may obtain, via a stochastic machine learning model based on the token embedding, an image related to the event. The system may generate, for display, the image and the event data. In some embodiments, the image may be deep-linked to functionality for submitting feedback relating to the event. The system may receive feedback related to the image indicating an invalid event. Based on the feedback related to the image, the system may perform a remedial action related to the token or to the event.

Abstract: Methods and systems are described herein for facilitating token use authentication for access tokens using stochastic images. The system may detect an authentication request to authenticate use of an access token. The access token may be associated with a first image previously displayed to an authenticated user of the access token. The system may retrieve the first image previously displayed to the authenticated user and input parameters previously used to generate the first image. The system may obtain, from a stochastic machine learning model based on the input parameters, a second image different from the first image. The system may generate, for display, an image set including the first image and the second image and may receive a selection of the first image from the image set. The system may then grant the authentication request based on the selection of the first image.

Abstract: Methods and systems are described herein for generating deep-linked stochastic image representations of access tokens that embed token access deep links on a mobile application interface. The system may obtain, in connection with a request to register an access token with an account, token data associated with the access token and event data associated with one or more events performed with the access token. The system may generate, for input to a stochastic machine learning model, input vectors using the token data and the event data. The system may obtain, via the stochastic machine learning model based on the input vectors, an image for the access token and may generate, for display on a user interface associated with the account, an image representation of the access token including the image and a deep link to functionality associated with the access token.