Fireeye, Inc.

Anchain.ai Inc.

Wei Quan

Chunsheng Victor Fang

Chunsheng Fang

Robert Venal

Raghunath Konda

Ben Wu

Han Xu

Benjamin Chang

Shuling He

Richard Lai

A method and apparatus that receive blockchain transaction data from a blockchain ledger to a transaction database, receive intelligence labels from a blockchain ecosystem intelligence database, select a blockchain transaction flow comprising blockchain transactions associated with a digital account source address, digital account intermediate addresses, a digital account destination address, and intermediate transactions, receive input trace parameters, where the input trace parameters include at least one of an objective directional setting, a tracing constraint, and a transaction filter, the transaction filter based on the transaction timestamps and the digital assets transferred, apply the intelligence labels to the digital account source address, the digital account intermediate addresses, and the digital account destination address, apply an artificial intelligence graph search algorithm to the blockchain transaction flow based on the input trace parameters, and generate a report including tracing destination summary statistics of the auto-traced path.

System and method for blockchain automatic tracing of money flow using artificial intelligence

A method involves receiving digital on blockchain information and digital off blockchain information. The digital data from the digital on blockchain information and the digital off blockchain information is extracted. The entity knowledge base engine contextualizes the relationships based on the digital data and the digital off blockchain information and the digital on blockchain information. The risk classification engine analyzes the digital data and transforms the digital data to an identified behavior category. The risk scoring regression engine analyzes the classified risk data and assigns a risk score to each classified risk data. The risk policy engine analyzes the classified risk data and determines if any deviations from rules or standards have or will occur. The security control system takes an action on the digital on blockchain information and digital off blockchain information based on the assigned risk score and any deviations from rules or standards.

System and method for blockchain transaction risk management using machine learning

A method for generating rule recommendation utilized in a creation of malware detection rules is described. Meta-information associated with a plurality of events collected during a malware detection analysis of an object by a cybersecurity system is received and a first plurality of features is selected from the received meta-information. Machine learning (ML) models are applied to each of the first plurality of features to generate a score that represents a level of maliciousness for the feature and thereby a degree of usefulness of the feature in classifying the object as malicious or benign. Thereafter, a second plurality of features is selected as the salient features, which are used in creation of the malware detection rules in controlling subsequent operations of the cybersecurity system. The second plurality of features being lesser in number that the first plurality of features.

System and method for automatically generating malware detection rule recommendations

A computerized method for reconfiguring one or more malware detection systems each performing cybersecurity analyses on incoming data is described. The method involves receiving meta-information including metrics associated with a malware detection system. Based on the meta-information, a determination is made whether the malware detection system is operating at an optimal performance level. If not, results produced by conducting behavior analyses predicting operability of the malware detection system are determined and the results are provided as feedback to the malware detection system to update one or more configuration parameter values thereof.

System and method for predicting and mitigating cybersecurity system misconfigurations

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Wei Quan