Abstract: A system includes a memory configured to store a set of private valid source data. The system includes processors operably coupled to the memory and configured to access the set of private valid source data, and to execute a dynamic data encryption engine configured to identify a sensitivity level of the set of private valid source data and to encrypt the set of private valid source data in accordance with a data encryption algorithm. The data encryption algorithm is selected based on the identified sensitivity level. The processors further execute a data ingestion and dynamic decryption engine configured to ingest the encrypted set of private valid source data into the hybrid cloud computing and storage system, and in response to receiving a request to retrieve the encrypted set of private valid source data from the hybrid cloud computing and storage system, decrypt the encrypted set of private valid source data.

Abstract: A system includes a memory configured to store a set of input data and processor operably coupled to the memory and configured to access the set of input data, execute a rule-based model configured to identify an encoding process, execute a first machine-learning model trained to encode the set of input data based on the encoding process and generate a reduced set of input data, transform the reduced set of input data from a one-dimensional probability distribution to a multidimensional probability distribution, execute a second machine-learning model trained to decode the reduced set of input data and generate a global set of input data based on the decoded reduced set of input data. In response to identifying a probable difference between the reduced set and the global set of input data, the processor is configured to identify the set of input data as corresponding to a set of misrepresentative data.

Abstract: A system includes a memory configured to store a set of private valid source data. The system includes processors operably coupled to the memory and configured to access the set of private valid source data, and to execute a dynamic data encryption engine configured to identify a sensitivity level of the set of private valid source data and to encrypt the set of private valid source data in accordance with a data encryption algorithm. The data encryption algorithm is selected based on the identified sensitivity level. The processors further execute a data ingestion and dynamic decryption engine configured to ingest the encrypted set of private valid source data into the hybrid cloud computing and storage system, and in response to receiving a request to retrieve the encrypted set of private valid source data from the hybrid cloud computing and storage system, decrypt the encrypted set of private valid source data.

Abstract: A system includes a memory configured to store a set of source data. The system further includes processors operably coupled to the memory and configured to access the set of source data, execute a first machine-learning model of one or more generative machine-learning models trained to generate a first set of data based on the set of source data, execute a second machine-learning model trained to identify the first set of data and a second set of data as each corresponding to one of a set of valid data or a set of invalid data, and execute a third machine-learning trained to identify the set of valid data as corresponding to one of a set of private valid data or a set of public valid data. The processors transmit the set of valid data to one of a first or second cloud computing and storage system based on the identification.

Abstract: A hybrid cloud orchestration process to move data from a private to a public cloud is disclosed. Requested data in a private cloud is analyzed to determine risk levels and whether it is fit for transfer based on an initial threat analysis. Data is encrypted by AES or RSA depending on data sensitivity. Redundant data and embedded threats are removed from the encrypted data without decryption. Encrypted data is hashed. Hash keys and hashed data are stored in a DHT distributed across nodes. Data requests from applications in the public cloud are validated by matching the request key with the unique hash key in the individual node containing the corresponding hash data. Data is returned to the application in the public cloud through an encrypted tunnel.

Abstract: Aspects of the disclosure relate to automatic script generation using a multi-layered ingestion program. An automatic ingestion platform may generate the program. The platform may receive a request to ingest information. The platform may automatically generate a plurality of executable scripts using the program. The plurality of scripts may include at least one script corresponding to a first layer of the program and a plurality of scripts corresponding to a second layer of the program. The platform may identify a subset of information to be ingested based on executing a script corresponding to the first layer. The platform may execute the scripts corresponding to the second layer. Executing the scripts corresponding to the second layer may cause the platform to deploy a schedule management program and transfer the subset of information to a third layer. The platform may cause synchronization of a central information repository with the third layer.

Abstract: Aspects of the disclosure relate to automatic script generation using a multi-layered ingestion program. An automatic ingestion platform may generate the program. The platform may receive a request to ingest information. The platform may automatically generate a plurality of executable scripts using the program. The plurality of scripts may include at least one script corresponding to a first layer of the program and a plurality of scripts corresponding to a second layer of the program. The platform may identify a subset of information to be ingested based on executing a script corresponding to the first layer. The platform may execute the scripts corresponding to the second layer. Executing the scripts corresponding to the second layer may cause the platform to deploy a schedule management program and transfer the subset of information to a third layer. The platform may cause synchronization of a central information repository with the third layer.

Abstract: Systems, methods, and apparatus are provided for expedited e-check processing via a universal clearance platform. In response to e-check initiation, a captured biometric marker may be uploaded to the clearance platform along with the e-check data. The platform may mint the biometric marker and e-check data as NFTs. The platform may insert the NFTs as a key-value pair in an integrated DHT. The biometric marker may be the key and the e-check data may be stored as the corresponding value. The platform may validate the key against previously captured biometric information and map the validated key to the corresponding value via an overlay network associated with the DHT. The platform may validate the retrieved e-check data against a previously captured transaction history to clear the e-check. In response to e-check clearance, the platform may route the e-check data to the ACH network to complete the transfer.

Abstract: Aspects of the disclosure relate to automatic script generation using a multi-layered ingestion program. An automatic ingestion platform may generate the program. The platform may receive a request to ingest information. The platform may automatically generate a plurality of executable scripts using the program. The plurality of scripts may include at least one script corresponding to a first layer of the program and a plurality of scripts corresponding to a second layer of the program. The platform may identify a subset of information to be ingested based on executing a script corresponding to the first layer. The platform may execute the scripts corresponding to the second layer. Executing the scripts corresponding to the second layer may cause the platform to deploy a schedule management program and transfer the subset of information to a third layer. The platform may cause synchronization of a central information repository with the third layer.

Abstract: A hybrid cloud orchestration process to move data from a private to a public cloud is disclosed. Requested data in a private cloud is analyzed to determine risk levels and whether it is fit for transfer based on an initial threat analysis. Data is encrypted by AES or RSA depending on data sensitivity. Redundant data and embedded threats are removed from the encrypted data without decryption. Encrypted data is hashed. Hash keys and hashed data are stored in a DHT distributed across nodes. Data requests from applications in the public cloud are validated by matching the request key with the unique hash key in the individual node containing the corresponding hash data. Data is returned to the application in the public cloud through an encrypted tunnel.

Abstract: Systems, methods, and apparatus are provided for expedited e-check processing via a universal clearance platform. In response to e-check initiation, a captured biometric marker may be uploaded to the clearance platform along with the e-check data. The platform may mint the biometric marker and e-check data as NFTs. The platform may insert the NFTs as a key-value pair in an integrated DHT. The biometric marker may be the key and the e-check data may be stored as the corresponding value. The platform may validate the key against previously captured biometric information and map the validated key to the corresponding value via an overlay network associated with the DHT. The platform may validate the retrieved e-check data against a previously captured transaction history to clear the e-check. In response to e-check clearance, the platform may route the e-check data to the ACH network to complete the transfer.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for dynamically altering pre-defined threshold restrictions for resource distributions, depending on results of analysis of one or more user environment factors. The invention is generally comprised of a deployable layer of intelligent models trained to response to user situations where unrestricted resource distribution may be allowed. The resulting service has ability to effectively authorize resource distribution and provide increased convenience for the user.

Abstract: Intelligent analysis and prognosis-based data partitioning orchestration for optimizing database performance. Partitioning is not limited to partitioning keys established solely based on the columns of the table being partitioned, rather analysis is undertaken on dependent tables and the past behavior of fundamental data elements in the database is assessed as a means for determining the most optimal partitioning scheme. Thus, relevant information and values in the table being partitioned, as well as dependent tables and the fundamental data elements is used to determine how likely each record/row in the table is to be subjected to a data manipulation operation. The likelihood of a data manipulation operation being performed on each record serves as the basis for assigning the record to one of a plurality of partitions.

Abstract: Intelligent analysis and prognosis-based data partitioning orchestration for optimizing database performance. Partitioning is not limited to partitioning keys established solely based on the columns of the table being partitioned, rather analysis is undertaken on dependent tables and the past behavior of fundamental data elements in the database is assessed as a means for determining the most optimal partitioning scheme. Thus, relevant information and values in the table being partitioned, as well as dependent tables and the fundamental data elements is used to determine how likely each record/row in the table is to be subjected to a data manipulation operation. The likelihood of a data manipulation operation being performed on each record serves as the basis for assigning the record to one of a plurality of partitions.