Abstract: Methods of verifying a user's identity using trusted members of the user's community are provided. Users may request trusted friends and family members register as vouching users. If a user needs to confirm the user's identity, such as during a multifactor authentication verification or in the event of a forgotten credential, vouching users may be called upon to verify user identity. Vouching users may confirm a user's identity via a group communication session or by proving physical proximity to the user. Physical proximity may be proven by tapping a token, such as an electronic device or a transaction card, to either the user's device and/or the vouching user's device. Using trusted friends and family members to verify a user's identity safeguards online accounts from deep fake AI creations and protects susceptible online users from phishing schemes and social engineering attacks.

Abstract: Systems and methods for distributing a transaction among multiple parties are provided. In exemplaray embodiments where users have two or more contactless cards, each card can be tapped to a user device, and a user device application can receive payment information from each card. The user device application can transmit payment information from each card to one selected card. The selected card can then transmit payment information from each card, including its own payment information, to a payment processor.

Abstract: Methods of verifying a user's identity using trusted members of the user's community are provided. Users may request trusted friends and family members register as vouching users. If a user needs to confirm the user's identity, such as during a multifactor authentication verification or in the event of a forgotten credential, vouching users may be called upon to verify user identity. Vouching users may confirm a user's identity via a group communication session or by proving physical proximity to the user. Physical proximity may be proven by tapping a token, such as an electronic device or a transaction card, to either the user's device and/or the vouching user's device. Using trusted friends and family members to verify a user's identity safeguards online accounts from deep fake AI creations and protects susceptible online users from phishing schemes and social engineering attacks.

Abstract: Systems and methods for generating directional information, including detecting an occurrence of a first trigger event, upon detecting the occurrence of the first trigger event, generating a first search query based on a predicted object, determining a target object based on the first search query, determining a recommended navigation path to the target object, generating a first graphical user interface (GUI) based on the recommended navigation path, and causing to display the first GUI.

Abstract: Methods, systems, and apparatuses are described herein for authenticating access to an account using questions which allow users to provide textual information about transactions conducted by an account. A machine learning model may be trained to predict the guessability of merchants. A request for access to an account may be received, and transaction data for that account may be received. An authentication question may be presented. For example, a user may be prompted to list places they have shopped recently. A user response comprising text data may be received. The text data may be processed to identify one or more merchants. If the one or more merchant(s) are represented in the transaction data, the machine learning model may be used to determine the guessability of the one or more merchants. An authentication score may be determined based on the guessability, and access to the account may be provided.

Abstract: In some implementations, a device may receive information indicating a set of parameters for a partition of a decentralized autonomous organization (DAO) implemented by a distributed database. The set of parameters may include a first parameter indicating a condition for completion of the partition and a second parameter indicating a digital asset wallet of a recipient that is to receive digital assets associated with the partition upon completion of the partition. The device may cause a smart contract, associated with the partition, to be added to the distributed database. The smart contract may include executable code that codifies the set of parameters. The smart contract may be configured to cause, responsive to satisfaction of the condition for completion of the partition, a record to be added to an additional distributed database indicating an association between a digital asset wallet of the partition and the digital asset wallet of the recipient.

Abstract: Aspects described herein may provide techniques for authenticating a user using transaction-based authentication questions that are generated based on item-level purchase data. The item-level purchase data of a transaction may include specific details of a transaction such as identification of each item purchased and corresponding prices paid for each item. Transaction-based authentication questions for a financial account may be generated based on the item-level purchase data that an authorized user of the financial account is likely to remember and that a malicious actor is unlikely to correctly guess. As a result, the authorized user of the account is likely to be correctly authenticated while the malicious actor is likely to answer the transaction-based authentication question incorrectly. Authentication can therefore effectively block malicious actors without overly burdening actual authorized users during the authentication process.

Abstract: Methods, systems, and apparatuses are described herein for authenticating access to an account using questions which allow users to provide textual information about transactions conducted by an account. A machine learning model may be trained to predict the guessability of merchants. A request for access to an account may be received, and transaction data for that account may be received. An authentication question may be presented. For example, a user may be prompted to list places they have shopped recently. A user response comprising text data may be received. The text data may be processed to identify one or more merchants. If the one or more merchant(s) are represented in the transaction data, the machine learning model may be used to determine the guessability of the one or more merchants. An authentication score may be determined based on the guessability, and access to the account may be provided.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving a permission from at least one user of a plurality of users to monitor at least one location associated with a device, utilizing a machine learning algorithm to automatically authenticate at least one action associated with the device based on at least one data beacon generating a primed signal; transmitting a plurality of data from the device to an external data source associated with the at least one action within a predetermined period of time based on the location of the device and the primed signal; and dynamically updating a storage module associated with the device with metadata based on a transmission of the plurality of data associated with the at least one action.

Abstract: Methods and systems for limiting resource access based on user input using an authentication token. In some aspects, the authentication token receives user input indicating a first allocation for a first resource access to be executed at a first time. The authentication token generates recommendations for a second allocation related to the first allocation. The user selects a second allocation. At the first time, the authentication token receives a first resource access request and executes the first allocation. The authentication token also transmits first metadata to an access approval system. At the second time, in response to a second resource access request, the authentication token or the access approval system compares the second resource access request to the first metadata or the second allocation to approve or decline the second resource access request.

Abstract: Aspects described herein may provide techniques for authenticating a user using transaction-based authentication questions that are generated based on item-level purchase data. The item-level purchase data of a transaction may include specific details of a transaction such as identification of each item purchased and corresponding prices paid for each item. Transaction-based authentication questions for a financial account may be generated based on the item-level purchase data that an authorized user of the financial account is likely to remember and that a malicious actor is unlikely to correctly guess. As a result, the authorized user of the account is likely to be correctly authenticated while the malicious actor is likely to answer the transaction-based authentication question incorrectly. Authentication can therefore effectively block malicious actors without overly burdening actual authorized users during the authentication process.

Abstract: Methods of verifying a user's identity using trusted members of the user's community are provided. Users may request trusted friends and family members register as vouching users. If a user needs to confirm the user's identity, such as during a multifactor authentication verification or in the event of a forgotten credential, vouching users may be called upon to verify user identity. Vouching users may confirm a user's identity via a group communication session or by proving physical proximity to the user. Physical proximity may be proven by tapping a token, such as an electronic device or a transaction card, to either the user's device and/or the vouching user's device. Using trusted friends and family members to verify a user's identity safeguards online accounts from deep fake AI creations and protects susceptible online users from phishing schemes and social engineering attacks.

Abstract: Methods, systems, and apparatuses are described herein for improving computer authentication processes through excluding fraudulent transactions in transaction-based authentication. A computing device may receive a request for access to an account from a user. The computing device may provide transaction data to a machine learning model. The computing device may receive data indicating a confidence threshold associated with the user from the machine learning model. The computing device may generate a modified set of merchant choices for the user by excluding merchants related to potentially fraudulent transactions within a predetermined time period. An authentication question may be generated, and access to the account may be provided based on a response to the authentication question.

Abstract: Methods, systems, and apparatuses are described herein for improving computer authentication processes through excluding fraudulent transactions in transaction-based authentication. A computing device may receive a request for access to an account from a user. The computing device may provide transaction data to a machine learning model. The computing device may receive data indicating a confidence threshold associated with the user from the machine learning model. The computing device may generate a modified set of merchant choices for the user by excluding merchants related to potentially fraudulent transactions within a predetermined time period. An authentication question may be generated, and access to the account may be provided based on a response to the authentication question.

Abstract: Aspects described herein may obfuscate publicly available personal information by publishing generated synthetic user personal data to one or more sites. By publishing the generated synthetic personal data to one or more sites, a user's actual personal data will be more difficult to discern and/or detect, resulting in greater privacy, security, and/or control of personal information. A machine learning model may be trained to generate synthetic personal data based on verified personal data and/or training datasets. Upon receiving a request from a user, the machine learning model may generate synthetic personal data, which appears similar to the publicly available information but includes false and/or inaccurate data and/or information about the user. The generated synthetic personal data and/or information may be disseminated to a plurality of sites to hide, or otherwise obfuscate, the user's actual data and/or information.

Abstract: Systems and methods are directed to optimizing a security and recoverability trade-off generally associated with cryptocurrency master key storage. Exemplary embodiments provide a biometrically derived cryptographic seed using a measurement of one or more scale invariant biometric attributes associated with a user. The measured user biometric data is then processed into a repeatable biometric identifier and formatted into a (biometric) cryptographic seed, for derivation of a master extended private key, which may be stored in an HD wallet or used dynamically to conduct a blockchain transaction. The biometric seed and master key generation process may be facilitated by a mobile application responsive to a readout of biometric data from sensors integrated/associated with the mobile device.

Abstract: In certain embodiments, token data may be generated, updated, and presented on a token display of a token. In some embodiments, a communication session may be initiated between a token and a terminal. Authentication data stored on the token may be replaced with updated authentication data. Updated token data may be generated based on updated authentication data. The token data on an electrophoretic display may be replaced with the updated token data.

Abstract: Techniques for improved management of data may include the aggregation of connections with data sources, the aggregation of data, and/or the dynamic caching of data using data caching models. The caching model(s) may be adaptable based on data characteristics, user information, and/or usage information.

Abstract: The invention relates to generating cryptographic tokens based on characteristic determination. The system may generate and transmit a request for encrypted records from a blockchain node, receive the encrypted records from the blockchain node, decrypt the encrypted records into payload identifiers, retrieve sets of item identifiers based on the payload identifiers, determine characteristics associated with the sets of items, and generate a new cryptographic token that indicates the characteristics.

Abstract: Systems and methods for recovery access to lost blockchain wallet seed phrases are disclosed. The systems and methods can store seed phrases for users for future retrieval. In some examples, a decentralized oracle creates an oracle private key that can be used to authenticate a user who is requesting the seed phrase. In some examples, the oracle creates a private/public key pair that can be used to transmit and store an encrypted version of the seed phrase. The authentication steps described herein also include knowledge-based authentication questions about the wallet, e.g., prior transactions using the wallet, value of the wallet, and the like.