Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a permission from the user to monitor a plurality of activities executed within the computing device; continually monitoring the plurality of activities executed within the computing device for a predetermined period of time; identifying an indication of an incoming interaction session within the predetermined period of time; automatically verifying a session interaction parameter associated with the incoming interaction session; determining a plurality of inquires associated with the research interaction session based on the at least one session interaction parameter; identifying the plurality of demographic informational items associated with the user; and automatically updating the programmable GUI element to display the plurality of inquires associated with the interaction session and the plurality of demographic informational items associated with the user.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a trained spam upsurge detection machine learning model that determines when a current frequency associated with spam communications received by a current user exceeds a baseline frequency associated with the current user; receiving a permission indicator identifying a permission by the user to detect communications being received by the computing device; receiving an indication of at least one communication being received; determining the at least one communication as a particular spam communication; updating a frequency at which spam communications have been received by the user based at least in part on the particular spam communication; utilizing the trained spam upsurge detection machine learning model to determine that the frequency exceeds a baseline frequency associated with the user; and initiating a scan of one or more dark web resources.

Abstract: In some implementations, a transaction card may include a card body having a first surface and a second surface opposite the first surface. The transaction card may include an integrated circuit (IC) chip embedded in the card body, and a plurality of first electrical contact sets electrically accessible from the first surface of the card body, where the plurality of first electrical contact sets have electrical connections to the IC chip. The transaction card may include a plurality of first magnetic stripe areas readable from the first surface of the card body. The transaction card may include a plurality of second electrical contact sets electrically accessible from the second surface of the card body, where the plurality of second electrical contact sets have electrical connections to the IC chip. The transaction card may include a plurality of second magnetic stripe areas readable from the second surface of the card body.

Abstract: The present disclosure provides an exemplary method, system, and computing device that may include the steps of receiving a first indication that information of a user has been detected at one or more dark web resources; classifying the item of the compromised information into an information type category; receiving a permission indicator to detect communications by the computing device; receiving a second indication of a communication; receiving a third indication that the user engages an interaction with the communication; instructing the computing device to execute a technique to obtain data for the communication; receiving the data for the communication; determining the communication is a spam communication; determining a current information type category being discussed during the spam communication; making a determination that the current information type category corresponds to the information type category; and instructing a graphical user interface to display an alert to the user.

Abstract: A computer-implemented method comprising: instructing a computing device to obtain a permission from the user to monitor a plurality of activities executed within the computing device; receiving a call session request from a computing device associated with a second user; utilizing a trained machine learning algorithm to confirm an identity of the user based on the call session interaction parameter to confirm the call interaction session as a verified call interaction session; generating a fictitious call session interaction parameter that differs from the at least one call session interaction parameter; modifying the call session request into a verified call session request by replacing the call session interaction parameter with the fictitious call session interaction parameter; utilizing a telecommunication network to transmit the verified call session request with the at least one fictitious session interaction parameter to the first calling-enabled computing device; automatically instructing the first c

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving input data from at least one external data aggregator; utilizing a trained machine learning algorithm to generate a database of known queries; receiving subsequent input data from the at least one external aggregator; automatically updating the database of known queries associated with the plurality of users; utilizing the trained machine learning algorithm to perform a cross-reference analysis to determine a presence of a data record within the database of known queries; dynamically removing the data record from the database of known queries; utilizing the trained machine learning algorithm to predict a trigger associated with the presence of the at least one data record; and instructing a computing device to initiate a verification of the presence of the at least one data record.

Abstract: Systems and methods of location-aware caller identification via machine learning techniques are disclosed. In one embodiment, an exemplary computer-implemented method may include: utilizing a trained call annotation machine learning model to determine one or both of an annotating condition and annotating location granularity, and associate one location of a user with one phone number of the user based at least on one or both of the annotating condition and the annotating location granularity; receiving second transactional information of one transaction associated with a first user; extracting second location information from the second transactional information of the one transaction; utilizing the trained call annotation machine learning model to automatically annotate one phone number record of one phone number of the first user, with the second location information at the annotating location granularity to form at least one user-specific location-specific annotated phone number record.

Abstract: In some implementations, a system may receive, at a front-end device and from an augmented reality (AR) device associated with a user, a request to use the front-end device. The system may transmit, to the AR device, a request to access an optical sensor of the AR device. The system may receive, from the AR device, an output, from the optical sensor, that indicates a hand gesture performed by the user of the AR device. Accordingly, the system may determine, based on the hand gesture, a corresponding input key of the front-end device. The system may perform an action based on the corresponding input key.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a permission from the user to monitor a plurality of activities executed within the computing device; receiving monitoring data of the activities executed within the plurality of computing devices for a predetermined period of time; identifying incoming interaction sessions across the plurality of computing devices; verifying one common session parameter associated with the incoming interaction sessions to identify the incoming interaction sessions as suspect interaction sessions; determining a frequency metric for the suspect interaction sessions; determining a threshold value for the frequency metric; receiving new monitoring data; determining that the new incoming interaction session has at least one common session interaction parameter with the suspect interaction sessions; automatically generating an interaction notification for transmission to the computing device; receiving a response to the int

Abstract: A cast structure configured to support a suspension arm and motor mount assembly for a vehicle is disclosed. The cast structure comprises a first fixing point attachable to a first mounting feature of a first crossmember of a vehicle frame, a first feature configured to receive the suspension arm of the vehicle in an assembled configuration, and a first portion configured to support a motor of the vehicle in an assembled configuration.

Abstract: The various implementations described herein include a video camera assembly that includes: (1) a housing; (2) an image sensor encased in the housing and configured to capture activity of the smart home environment; (3) a wireless radio configured to transmit video frames captured by the image sensor to an electronic device via a remote server; (4) at least one infrared transmitter configured to selectively illuminate the smart home environment; (5) one or more circuit boards encased in the housing, the one or more circuit boards including at least one processor mounted thereon; and (6) a heating component coupled to the image sensor, the heating component configured to continuously maintain the image sensor at a temperature above a threshold temperature while the image sensor is capturing the activity of the smart home environment.

Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.

Abstract: Described herein are techniques are provided for enabling a security orchestration, automation, and response (SOAR) service to automatically manage apps used to interface with an integrated security operations service and other related devices and services. Further described herein is a SOAR app generator service or application used to automate the creation of apps for a SOAR service based on application programming interfaces (API) specifications for related devices or services, as well as visual playbook editor interfaces for a SOAR service that enable the configuration of complex action input parameters including arrays and objects.

Abstract: The various implementations described herein include a video camera assembly that includes: (1) a housing; (2) an image sensor positioned within the housing and having a field of view corresponding to a scene in the smart home environment; and (3) a concave-shaped front face positioned in front of the image sensor such that light from the scene passes through the front face prior to entering the image sensor; where the front face includes: (a) an inner section corresponding to the image sensor; and (b) an outer section between the housing and the inner section, the outer section having a concave shape that extends from an outer periphery of the outer section to an inner periphery of the outer section; and where the concave shape extends around an entirety of the outer periphery.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving input data from at least one external data aggregator; utilizing a trained machine learning algorithm to generate a database of known queries; receiving subsequent input data from the at least one external aggregator; automatically updating the database of known queries associated with the plurality of users; utilizing the trained machine learning algorithm to perform a cross-reference analysis to determine a presence of a data record within the database of known queries; dynamically removing the data record from the database of known queries; utilizing the trained machine learning algorithm to predict a trigger associated with the presence of the at least one data record; and instructing a computing device to initiate a verification of the presence of the at least one data record.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a permission to monitor a plurality of activities executed within the second computing device; continuously monitoring the plurality of activities executed within the second computing device for a predetermined period of time; receiving an indication of an incoming interaction session within the predetermined period of time; automatically verifying at least one session interaction parameter associated with the incoming interaction session to identify the incoming interaction session as a suspect interaction session; determining when a duration of time associated with the suspect interaction session meets or exceeds a predetermined duration threshold; utilizing a trained detection machine learning model to model a confidence value associated with the suspect interaction session; identifying at least one future activity subsequent to the suspect interaction session; and automatically instructing the firs

Abstract: In some embodiments, validation of network operations related to use of a token via a token request based on entity characteristics may be facilitated. In some embodiments, a token request indicating use of a token to access an item associated with an entity may be detected, where the token is bound to one or more entity characteristics. Based on the token request, an entity identifier associated with the entity may be obtained. Using the entity identifier, one or more item characteristics of items available via the entity may be determined. Determining whether the entity satisfies the one or more entity characteristic to which the token is bound may be determined based on the one or more item characteristics. Access to the item associated with the entity may be validated based on the determination indicating that the entity satisfies the one or more entity characteristics to which the token is bound.

Abstract: Aspects discussed herein may relate to techniques for authenticating a user using transaction-based authentication questions. The transaction-based authentication questions may be provided to the user. The user may provide audible responses to the transaction-based authentication questions that may be captured by a smart device, such as an always on listening device. Authentication of the user may be based on voice analysis of the audible responses to the transaction-based authentication questions and/or based on the answers to the transaction-based authentication questions.

Abstract: A mount adapter assembly for facilitating attachment of articles to a mounting rack includes a first element and a second element. The first element is shaped substantially complementary to at least a first portion of an orifice positioned in a mounting rack. The first element is at least partially insertable into the first portion of the orifice from a first face of the mounting rack. The second element can abut the mounting rack from a second face of the mounting rack. A connector engages the first element to the second element so that the first element and the second element are coupled to the mounting rack. A fastener engaged to the first element can engage a substrate so that the substrate is coupled to the mounting rack. The substrate can be used to attach a variety of articles to the mounting rack.

Abstract: A mount adapter assembly for facilitating attachment of articles to a mounting rack includes a first element and a second element. The first element is shaped substantially complementary to at least a first portion of an orifice positioned in a mounting rack. The first element is at least partially insertable into the first portion of the orifice from a first face of the mounting rack. The second element can abut the mounting rack from a second face of the mounting rack. A connector engages the first element to the second element so that the first element and the second element are coupled to the mounting rack. A fastener engaged to the first element can engage a substrate so that the substrate is coupled to the mounting rack. The substrate can be used to attach a variety of articles to the mounting rack.