Abstract: Systems and methods for novel uses and/or improvements to blockchains and blockchain technology. As one example, systems and methods are described herein for self-validating digital records that may be transferred in real-time through a cross-network registry. For example, in a conventional system, minting a token (e.g., a digital record) involves writing a self-executing program that defines the transfer rules of the digital record. Once the self-executing program is written, it is deployed on a blockchain, and the digital record is minted by publishing it to a blockchain.

Abstract: Systems and methods for a bifurcated self-executing program that wraps a first self-executing program (e.g., a first smart contract) on a blockchain within a second self-executing program (e.g., a second smart contract), in which the second self-executing program enforces the requirement for particular security credentials/certificates. The bifurcated self-executing program comprises a single compiled self-executing program that combines the first self-executing program and the second self-executing program.

Abstract: Systems and methods for a bifurcated self-executing program that wraps a first self-executing program (e.g., a first smart contract) on a blockchain within a second self-executing program (e.g., a second smart contract), in which the second self-executing program enforces the digital signature requirement. The bifurcated self-executing program comprises a single compiled self-executing program that combines the first self-executing program and the second self-executing program.

Abstract: Systems and methods for a bifurcated self-executing program that wraps a first self-executing program (e.g., a first smart contract) on a blockchain within a second self-executing program (e.g., a second smart contract), in which the second self-executing program enforces the requirement for particular security credentials/certificates. The bifurcated self-executing program comprises a single compiled self-executing program that combines the first self-executing program and the second self-executing program.

Abstract: A computer-implemented method comprising receiving a transaction request from a first computing device, the transaction request corresponding to a pending transaction between the first computing device and a second computing device and comprising a first set of transaction attributes; appending block instances to blockchains of the first and second computing devices, retrieving or receiving, from the second computing device, a second set of transaction attributes; when the first set of transaction attributes match, identifying a second blockchain associated with the pending transaction; automatically executing a protocol to compare the first set of transaction attributes with data stored onto a ledger of the identified second blockchain; and, in response to determining that the first set of transaction attributes complies with data of the ledger of the identified second blockchain, appending block instance to the blockchain comprising data corresponding to the transaction request to blockchains of the first a

Abstract: A system configured to detect malware is described. The system configured to detect malware including a data collector configured to detect at least a first hypertext transfer object in a chain of a plurality of hypertext transfer objects. The data collector further configured to analyze at least the first hypertext transfer object for one or more events. And, the data collector configured to generate a list of events based on the analysis of at least the first hypertext transfer object.

Abstract: A system configured to detect malware is described. The system configured to detect malware including a data collector configured to detect at least a first hypertext transfer object in a chain of a plurality of hypertext transfer objects. The data collector further configured to analyze at least the first hypertext transfer object for one or more events. And, the data collector configured to generate a list of events based on the analysis of at least the first hypertext transfer object.

Abstract: A system configured to detect malware is described. The system including an infection verification pack configured to perform behavior detonation; identify a malware object based on machine-learning; and select one or more persistent artifacts of the malware on the target system based on one or more algorithms applied to behavior traces of the malware object to select one or more persistent artifacts of the malware on the target system.

Abstract: A system configured to detect malware is described. The system configured to detect malware including a data collector configured to detect at least a first hypertext transfer object in a chain of a plurality of hypertext transfer objects. The data collector further configured to analyze at least the first hypertext transfer object for one or more events. And, the data collector configured to generate a list of events based on the analysis of at least the first hypertext transfer object.

Abstract: A system configured to detect malware is described. The system configured to detect malware including a data collector configured to detect at least a first hypertext transfer object in a chain of a plurality of hypertext transfer objects. The data collector further configured to analyze at least the first hypertext transfer object for one or more events. And, the data collector configured to generate a list of events based on the analysis of at least the first hypertext transfer object.

Abstract: A system configured to detect malware is described. The system configured to detect malware including a data collector configured to detect at least a first hypertext transfer object in a chain of a plurality of hypertext transfer objects. The data collector further configured to analyze at least the first hypertext transfer object for one or more events. And, the data collector configured to generate a list of events based on the analysis of at least the first hypertext transfer object.

Abstract: A system configured to detect malware is described. The system including an infection verification pack configured to perform behavior detonation; identify a malware object based on machine-learning; and select one or more persistent artifacts of the malware on the target system based on one or more algorithms applied to behavior traces of the malware object to select one or more persistent artifacts of the malware on the target system.