Abstract: A device participates in a cyclical collaboration system. The device receives a request from a third party. A request value is determined that is associated with the request. A first random number is determined based on the first request value. The first random number is provided to a downstream device. A second random number is received that is generated by a upstream device. A first encrypted request value is determined based on the first request value, the first random number, and the second random number. The first encrypted request value is provided to a multiple party encryption subsystem. Encrypted request values generated by other participants of the cyclical collaboration network are received from the multiple party encryption subsystem. A validation score is determined based on the first encrypted request values and the encrypted request values received from the multiple party encryption subsystem.

Abstract: A system for detecting data leakage is disclosed. The system intercepts web traffic data, de-duplicates the web traffic data, and extracts data elements from the web traffic data. The system further groups the data elements into multiple clusters based on data types associated with the data elements. The system then identifies data elements in a cluster that were previously sent to a user and identifies allowed data elements from an allow table that are supposed to be sent to the user. The system determines whether there is a data leakage by determining whether the identified data elements in the cluster comprises at least one data element that is not in the identified allowed data elements in the allow table.

Abstract: An apparatus includes a memory and a processor. The memory stores a time-series of data sets, and a first version of a data structure generated from the time-series as it existed at a first time. The data structure includes a terminal node that stores a compressed representation of the time-series and a bottom level of nodes, each of which stores a hash of a data set of the time-series. The processor generates a second version of the data structure based on the time-series as it exists at a second time. The processor determines that the data stored by the terminal nodes in the first and second versions do not match. In response, the processor identifies a bottom level node for which the stored data in the first and second versions do not match, and requests validation. The processor receives a response indicating whether an intentional change was made.

Abstract: An apparatus includes a memory and a processor. The memory stores a time-series of data sets, and a first version of a data structure generated from the time-series as it existed at a first time. The data structure includes a bottom level of nodes, and subsequent levels of nodes, ending with a top level terminal node. Each bottom level node stores a hash of an assigned time-series data set. Each node of each subsequent level stores data generated from an assigned group of nodes of a previous level. The processor receives a validation request. In response, the processor generates a second version of the data structure based on the time-series as it exists at a second time. The processor determines that the terminal nodes in the first and second versions of the data structure do not match. In response, the processor generates an alert.

Abstract: An apparatus includes a memory and a processor. The memory stores a time-series of data sets, and a first version of a data structure generated from the time-series as it existed at a first time. The data structure includes a bottom level of nodes, and subsequent levels of nodes, ending with a top level terminal node. Each bottom level node stores a hash of an assigned time-series data set. Each node of each subsequent level stores data generated from an assigned group of nodes of a previous level. The processor receives a validation request. In response, the processor generates a second version of the data structure based on the time-series as it exists at a second time. The processor determines that the terminal nodes in the first and second versions of the data structure do not match. In response, the processor generates an alert.

Abstract: An apparatus includes a memory and a processor. The memory stores a time-series of data sets, and a first version of a data structure generated from the time-series as it existed at a first time. The data structure includes a terminal node that stores a compressed representation of the time-series and a bottom level of nodes, each of which stores a hash of a data set of the time-series. The processor generates a second version of the data structure based on the time-series as it exists at a second time. The processor determines that the data stored by the terminal nodes in the first and second versions do not match. In response, the processor identifies a bottom level node for which the stored data in the first and second versions do not match, and requests validation. The processor receives a response indicating whether an intentional change was made.

Abstract: An intrusion detection system that includes a processor configured to receive HyperText Transfer Protocol (HTTP) data and to convert the HTTP data into a data tree object that links field values from the HTTP data. The processor is further configured to identify a field value from the data object tree and to determine a set of feature values for the field value corresponding with input features for the neural network model. The processor is further configured to apply the determined set of feature values to the neural network model to generate an attack vector array. The attack vector array includes flag bits that each correspond with an attack type. The processor is further configured to trigger an event in response to determining that at least one flag bit is set.

Abstract: Embodiments of the present invention provide a system for executing, securing, and non-repudiation of pooled conditional smart contracts over a distributed blockchain network. In particular, the system may receive an instrument request from a beneficiary entity, where the instrument request includes an instrument amount. The system can then identify a lead contribution amount that a lead entity is willing to provide to meet a portion of the instrument amount. A set of supporting entities can be identified as willing to provide supporting contribution amounts to meet the remainder of the instrument amount. A conditional contract can be sent to each supporting entity that, when signed, authorizes the system to transfer contribution amounts, which may be in the form of cryptocurrency, from blockchain addresses of the lead and supporting entities to a blockchain address of the beneficiary entity. Once the instrument amount has been secured, the system executes the transactions.

Abstract: A device participates in a cyclical collaboration system. The device receives a request from a third party. A request value is determined that is associated with the request. A first random number is determined based on the first request value. The first random number is provided to a downstream device. A second random number is received that is generated by a upstream device. A first encrypted request value is determined based on the first request value, the first random number, and the second random number. The first encrypted request value is provided to a multiple party encryption subsystem. Encrypted request values generated by other participants of the cyclical collaboration network are received from the multiple party encryption subsystem. A validation score is determined based on the first encrypted request values and the encrypted request values received from the multiple party encryption subsystem.

Abstract: A system is provided for exchanging data using Electronic Data Interchange (EDI). A transmitting entity obtains an EDI file from a document that is to be transmitted to a destination server and adds routing information to the EDI file based on a first routing configuration, wherein the routing information is to be used by the receiving entity for routing the EDI file to the destination server. The receiving entity receives the EDI file from the transmitting entity and extracts the routing information from the EDI file. The receiving entity determines the destination server from a second routing configuration based on the extracted routing information and forwards the EDI file to the destination server.

Abstract: An apparatus includes a memory and a hardware processor. The memory stores a private encryption key. The processor intercepts a first transaction request from a user, communicates a first recertification request to a certificate authority that issued the private encryption key, and receives, from the certificate authority, a first message indicating that the private encryption key is valid for use. In response to the first message, the processor generates a first digital signature using the private encryption key, generates a first non-repudiation message comprising the first digital signature and the first message, generates a second message comprising the first transaction request and the first non-repudiation message, and communicates the second message to a server to process the first transaction request.

Abstract: A system is provided for exchanging data using Electronic Data Interchange (EDI). A transmitting entity obtains an EDI file from a document that is to be transmitted to a destination server and adds routing information to the EDI file based on a first routing configuration, wherein the routing information is to be used by the receiving entity for routing the EDI file to the destination server. The receiving entity receives the EDI file from the transmitting entity and extracts the routing information from the EDI file. The receiving entity determines the destination server from a second routing configuration based on the extracted routing information and forwards the EDI file to the destination server.

Abstract: An intrusion detection system that includes a processor configured to receive HyperText Transfer Protocol (HTTP) data and to convert the HTTP data into a data tree object that links field values from the HTTP data. The processor is further configured to identify a field value from the data object tree and to determine a set of feature values for the field value corresponding with input features for the neural network model. The processor is further configured to apply the determined set of feature values to the neural network model to generate an attack vector array. The attack vector array includes flag bits that each correspond with an attack type. The processor is further configured to trigger an event in response to determining that at least one flag bit is set.

Abstract: An intrusion detection system that includes a tree builder engine configured to receive HyperText Transfer Protocol (HTTP) data and to convert the HTTP data into a data tree object that links field values from the HTTP data. The system further includes a feature extractor engine configured to identify a field value from the data object tree and to determine a set of feature values for the field value corresponding with input features for the neural network model. The system further includes a neural network engine configured to apply the determined set of feature values to the neural network model to generate an attack vector array. The attack vector array includes flag bits that each correspond with an attack type. the system further includes an intrusion analyzer engine configured to trigger an event in response to determining that at least one flag bit is set.

Abstract: A system for detecting data leakage is disclosed. The system intercepts web traffic data, de-duplicates the web traffic data, and extracts data elements from the web traffic data. The system further groups the data elements into multiple clusters based on data types associated with the data elements. The system then identifies data elements in a cluster that were previously sent to a user and identifies allowed data elements from an allow table that are supposed to be sent to the user. The system determines whether there is a data leakage by determining whether the identified data elements in the cluster comprises at least one data element that is not in the identified allowed data elements in the allow table.

Abstract: A system for detecting data leakage is disclosed. The system intercepts web traffic data, de-duplicates the web traffic data, and extracts data elements from the web traffic data. The system further groups the data elements into multiple clusters based on data types associated with the data elements. The system then identifies data elements in a cluster that were previously sent to a user and identifies allowed data elements from an allow table that are supposed to be sent to the user. The system determines whether there is a data leakage by determining whether the identified data elements in the cluster comprises at least one data element that is not in the identified allowed data elements in the allow table.

Abstract: Embodiments of the present invention provide a system for executing, securing, and non-repudiation of pooled conditional smart contracts over a distributed blockchain network. In particular, the system may receive an instrument request from a beneficiary entity, where the instrument request includes an instrument amount. The system can then identify a lead contribution amount that a lead entity is willing to provide to meet a portion of the instrument amount. A set of supporting entities can be identified as willing to provide supporting contribution amounts to meet the remainder of the instrument amount. A conditional contract can be sent to each supporting entity that, when signed, authorizes the system to transfer contribution amounts, which may be in the form of cryptocurrency, from blockchain addresses of the lead and supporting entities to a blockchain address of the beneficiary entity. Once the instrument amount has been secured, the system executes the transactions.

Abstract: A system for generating user session objects is disclosed. The system intercepts web traffic data and extracts dynamic content items from the web traffic data such that the dynamic content items are separated from static content items. The system further groups the dynamic content items based on their associated user session IDs. The system then links together the dynamic content items of a group in sequence to generate a user session object, wherein the dynamic content items include one or more static content reference IDs associated with the static content items.

Abstract: An apparatus includes a memory and a hardware processor. The memory stores a private encryption key. The processor intercepts a first transaction request from a user, communicates a first recertification request to a certificate authority that issued the private encryption key, and receives, from the certificate authority, a first message indicating that the private encryption key is valid for use. In response to the first message, the processor generates a first digital signature using the private encryption key, generates a first non-repudiation message comprising the first digital signature and the first message, generates a second message comprising the first transaction request and the first non-repudiation message, and communicates the second message to a server to process the first transaction request.

Abstract: An intrusion detection system that includes a tree builder engine configured to receive HyperText Transfer Protocol (HTTP) data and to convert the HTTP data into a data tree object that links field values from the HTTP data. The system further includes a feature extractor engine configured to identify a field value from the data object tree and to determine a set of feature values for the field value corresponding with input features for the neural network model. The system further includes a neural network engine configured to apply the determined set of feature values to the neural network model to generate an attack vector array. The attack vector array includes flag bits that each correspond with an attack type. the system further includes an intrusion analyzer engine configured to trigger an event in response to determining that at least one flag bit is set.