Abstract: Creation and secure storage of non-fungible tokens (NFT) formed from derivatives of digital properties/assets within a branch of a distributed ledger that stores the original NFT. Each branch of the distributed ledger emanates from a data block of the trunk of the distributed ledger and stores an NFT formed from a derivative of the underlying digital property used to form the original NFT. Each NFT formed from the derivative of the digital property may include a smart contract that defines the parameters for the derivative and logic for determining resource compensation for the creator/owner of the original digital property/asset based on consumption of the derivative digital property/asset. Moreover, sub-branches may emanate from data blocks of the branches of the distributed ledger, with the sub-branches storing an NFT formed from a derivative of the derivative digital property/asset.

Abstract: Embodiments of the present invention provide a system for executing audio cryptology in real-time for audio misappropriation prevention. The system is configured for identifying, via a cryptographic device, one or more audio signals, causing the cryptographic device to generate and emit a dynamically varying continuous audio tone, continuously monitoring in real-time the one or more audio signals, via the cryptographic device, determining, via the cryptographic device, termination of the one or more audio signals based on continuously monitoring the one or more audio signals in real-time, and causing the cryptographic device to stop generating and emitting the dynamically varying continuous audio tone.

Abstract: A system for extracting a plurality of biometric indicators from a user profile stored in a memory of a server, wherein the plurality of biometric indicators is derived from the user using facial recognition and fingerprint analysis. The system embeds the extracted plurality of biometric indicators into an avatar associated with the user. Upon receiving a request from the avatar to access a virtual reality (VR) environment, the system determines one or more biometric indicators from the plurality of biometric indicators embedded into the avatar. The system determines a match by comparing the determined one or more biometric indicators with the corresponding biometric indicators from the user profile stored in the memory. In response to determining the match, the system authenticates the avatar and approves the request to allow the avatar to access the virtual environment.

Abstract: Authentication/verification of sub-environments that represent entities within an augmented/virtual reality computing network and virtual objects present in the sub-environment that represent individuals associated with the entity. In response to authentication, a sensory-perceptible indicator (e.g., visual, audible or haptic indicators) is presented to users of the virtual reality computing environment that notify the user that the entity or virtual objects representing the entity have been authenticated. Authentication may be performed via watermarks embedded in images present within the sub-environment, capturing and comparing physical characteristics of an authorized individual representing the entity, cryptographic frequency hopping and/or electromagnetic signatures.

Abstract: Aspects of the disclosure relate to predicting the spread of malicious software. The computing platform may identify malicious software at a computing device and may input characteristics of the malicious software into a machine learning model to produce time horizons for the malicious software. The computing platform may identify, using a knowledge graph and based on the time horizons, subsets of computing devices, each corresponding to a particular time horizon. The computing platform may perform, at a time within a first time horizon, a first security action for a first subset of computing devices within the first time horizon and a second security action for a second subset of computing devices located within a second time horizon, where the first time horizon and the second time horizon indicate that the first subset will be affected by the malicious software prior to the second subset.

Abstract: Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.

Abstract: A decoder is provided for decoding user information. The decoder obtains a random code pattern from at least one of a card or a device owned by a user. The decoder further obtains a personal identifier from the user. The decoder then queries a mapping table based on a combination of the random code pattern and the personal identifier of the user, wherein the mapping table comprises user information associated with each of a plurality of users mapped to a respective unique combination of a random code pattern and a personal identifier of the user. The decoder obtains user information of the user in response to the query, wherein one or more actions are performed based on the user information.

Abstract: A system is provided for partitioning digital resources using a networked resource platform. In particular, the system may generate digital resources using a customized set of executable code such that each digital resource may comprise one or more digital resource partitions. Each digital resource share may be associated with a cryptographic address. Upon receiving a request from a user to transfer the digital resource partitions, the system may execute various validation checks on the cryptographic address and the digital resource before executing the transfer. In this way, the system provides an efficient way to partition and transfer digital resources.

Abstract: Aspects of the disclosure relate to predicting the spread of malicious software. The computing platform may identify malicious software at a computing device and may input characteristics of the malicious software into a machine learning model to produce time horizons for the malicious software. The computing platform may identify, using a knowledge graph and based on the time horizons, subsets of computing devices, each corresponding to a particular time horizon. The computing platform may perform, at a time within a first time horizon, a first security action for a first subset of computing devices within the first time horizon and a second security action for a second subset of computing devices located within a second time horizon, where the first time horizon and the second time horizon indicate that the first subset will be affected by the malicious software prior to the second subset.

Abstract: A system is provided for monitoring real-time data inputs across multiple channels, determining potential impacts to a network or entity policy taxonomy, and taking one or more automated, responsive actions based on determined impacts. In this way, the system described herein is able to optimize system processes and system protections on an enterprise-wide scale in response to current events, policy or regulation changes, or predicted measures taken by private or public entities that may necessitate adaptation of one or more workflow processes or technology taxonomies, either upstream or downstream of the system itself.

Abstract: Aspects of the disclosure relate to using machine-learning models to determine graduated levels of access to secured data for remote devices. In some embodiments, a computing platform may establish a connection with a mobile device. Subsequently, based on establishing the connection, the platform may identify initial device information, device features, and user information. The platform may input the identified information into an authentication model to compute a baseline authentication score and then may identify an initial level of access to secured resources for the mobile device. Thereafter, the platform may receive from the mobile device, AR/VR device information captured by the mobile device. The platform may input the AR/VR device information into the authentication model to compute an augmented authentication score. Based on the augmented score, the platform may identify an augmented level of access to secured resources for the mobile device.

Abstract: Detecting malicious/spoofed Universal Resource Locators (URLs) and/or files in received electronic mail (i.e., email) and, in response to detection, automatically taking responsive measures to prevent interaction/access to the malicious/spoofed URLs and/or files and/or limit, network-wide, the exposure to the malicious/spoofed URLs and/or files. Valid URLs and/or files are assigned a token, such as an alpha-numeric passcode or the like and the assigned token is verified upon receipt of the email by the intended recipient. In the event that the token cannot be verified or a token is not received for a URL or file, the automated responsive actions ensue.

Abstract: Embodiments of the present invention provide a system for executing audio cryptology in real-time for audio misappropriation prevention. The system is configured for identifying, via a cryptographic device, one or more audio signals, causing the cryptographic device to generate and emit a dynamically varying continuous audio tone, continuously monitoring in real-time the one or more audio signals, via the cryptographic device, determining, via the cryptographic device, termination of the one or more audio signals based on continuously monitoring the one or more audio signals in real-time, and causing the cryptographic device to stop generating and emitting the dynamically varying continuous audio tone.

Abstract: Embodiments of the present invention provide a system for generating a real-time audio token for multi-factor audio authentication. The system is configured for determining that a user is accessing an entity resource, via a user device of the user, causing a cryptographic device associated with the user to generate and emit a dynamically varying continuous audio tone, performing authentication of the user based at least in part on the dynamically varying continuous audio tone, determining that the authentication based at least in part on the dynamically varying continuous audio tone is successful, and allowing the user to access the entity resource based on determining that the authentication based at least in part on the dynamically varying continuous audio tone is successful.

Abstract: A system is provided for implementing time-restricted access control to electronic digital resources. In some embodiments, the custom set of executable code used to generate the digital resource may provide granular control over access restrictions for accessing, viewing, and/or transferring the digital resource. Such access restrictions may include time duration restrictions, access frequency restrictions, data quality restrictions, and/or the like. In this way, the system may limit access to the digital resource in a secure manner.

Abstract: A system is provided for implementing transfer and access restrictions on electronic digital resources. In particular, the system may generate a digital resource on a distributed electronic data register using a custom set of executable code. Using the custom set of code, the generated digital resource may in some embodiments be an access restricted resource that may be controlled by one or more access and/or transfer restrictions. Accordingly, the system may require a user to provide valid authentication credentials in order to access and/or transfer the digital resource. In this way, the system may prevent the misuse of digital resource stored within the network environment.

Abstract: A system is provided for cryptographic hash-based reconstruction of electronic data files. In particular, the system may comprise a data reconstruction database containing entries for elements of electronic data files. Each element and/or entry within the data reconstruction database may be associated with a unique tag or identifier. Accordingly, when data files are generated and/or stored by the system, the data files may comprise an ordered list of one or more identifiers. Based on the identifiers with the data files, the system may dynamically reconstruct the contents of the data files. The system may further use cryptographic keys or hash values to provide secured access control to the data files. In this way, the system may provide an efficient and secure way to store and generate electronic data files and provide secured access thereto.

Abstract: A system is provided for remediating computing system breaches by reversibly distributing data to a plurality of edge points in a distributed network. In particular, the system may intelligently track network data to predict breach vector pathways and may track various types of network traffic data for computing systems within the network. Based on the network traffic data, the system may generate a network topology, mapping the various types of network connections across the computing systems in the network environment as well as the datasets that were transferred across such connections. In the event of a system breach, the system may divide each dataset into a plurality of partial data packets. The system may transmit each partial data packet to a different user device or computing device in the network. After the breach is remediated, the system may recall the individual data packets and reassemble the datasets for future use.

Abstract: Systems, computer program products, and methods are described herein for augmented hash-based portioning of non-fungible electronic resources for detection of unauthorized duplicates. The present invention is configured to receive an unauthorized duplication detection request for a first NFT from a first user; segment the first digital resource into a first set of resource portions; generate a first set of hash values corresponding to the first set of resource portions; retrieve a second digital resource, wherein the second digital resource is associated with a second NFT; segment the second digital resource into a second set of resource portions; generate a second set of hash values corresponding to the second set of resource portions; determine that the second digital resource is similar to the first digital resource; determine that the second NFT is an unauthorized duplication of the first NFT; and trigger one or more responsive actions.

Abstract: Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.