Abstract: Systems and methods for decrypting a HyperText Markup Language (“HTML”) are described. The method may include obtaining, via a browser module associated with a first user device, an encrypted HTML element; generating, via the browser module associated with the first user device, a first request to decrypt the encrypted HTML element; transmitting, via a processor, the first request and session data; obtaining, via the processor, a license for the encrypted HTML element, wherein the license include a decryption key and at least one rule; determining, via the processor, whether the encrypted HTML element satisfies the at least one rule of the license; upon determining the encrypted HTML element satisfies the at least one rule of the license, decrypting, via the processor, the encrypted HTML element using the decryption key; and causing to output, via a graphical user interface (GUI) associated with the first user device, the decrypted HTML element.

Abstract: Methods and systems are disclosed herein to recommend load rebalancing based on learned patterns of recurrence. In some aspects, the method receives a requested load usage from a user system and a load usage dataset. Each entry in the load usage dataset corresponds to an instance of load use. The method determines similar instances based on a respective amount and respective category of each entry. The method then clusters the similar instances into a first cluster and a second cluster based on frequencies of the similar instances. The method combines load uses corresponding to the first cluster into a first recurring load use and load uses corresponding to the second cluster into a second recurring load use. The method compares the requested load usage to the second recurring load use to generate a recommendation to the user system for rebalancing load usage.

Abstract: In some implementations, a system may receive interaction data associated with interactions between a user and subsets of a plurality of interaction parties. The system may store the interaction data and the as historical interaction data associated with historical interactions of the user. The system may provide the historical interaction data as input to a machine learning model, which may be trained using supervised learning and the historical interactions of the user or historical interactions of one or more other users with one or more of the plurality of interaction parties. The system may receive an output, based on applying the machine learning model to the historical interaction data, that may indicate one or more recommended interaction parties based at least in part on one or more factors, wherein the one or more recommended parties may be local entities local to a geographic location associated with the user.

Abstract: Methods and systems are described herein for an authentication mechanism that uses cryptographic tokens and eye-tracking data. In particular, the disclosed mechanism may receive an authentication request that includes an identifier of a cryptographic token and retrieve eye-tracking data and an image associated with the cryptographic token. The eye-tracking data may store various coordinates within the image and may be encoded for use in authentication. The disclosed mechanism may then transmit the image to a computing device (e.g., associated with a user) that is able to perform gaze detection as part of an authentication operation. In response, the disclosed mechanism may receive user gaze data collected during the authentication operation and determine whether the eye-tracking data matches the user gaze data. Based on determining that the eye-tracking data matches the user gaze data, the disclosed mechanism may transmit to the computing device an indication of successful authentication.

Abstract: The invention relates to generating cryptographic tokens based on received records. The system may receive a blockchain operation request comprising a plurality of records, encrypt a plurality of records into an encrypted payload, generate a cryptographic token based on the encrypted payload, and cause the cryptographic token to be committed to a blockchain.

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: In some implementations, a system may receive interaction data associated with interactions between a user and subsets of a plurality of interaction parties. The system may store the interaction data and the as historical interaction data associated with historical interactions of the user. The system may provide the historical interaction data as input to a machine learning model, which may be trained using supervised learning and the historical interactions of the user or historical interactions of one or more other users with one or more of the plurality of interaction parties. The system may receive an output, based on applying the machine learning model to the historical interaction data, that may indicate one or more recommended interaction parties based at least in part on one or more factors, wherein the one or more recommended parties may be local entities local to a geographic location associated with the user.