Utilizing machine learning to detect ransomware in code
AssigneeSaudi Arabian Oil Company
InventorsMaha Nasser Alasmari, Abdullah Abdulaziz Alturaifi, Sultan Saadaldean Alsharif
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AssigneeSaudi Arabian Oil Company
InventorsMaha Nasser Alasmari, Abdullah Abdulaziz Alturaifi, Sultan Saadaldean Alsharif
Estimating the term…
Implementations can provide a method that includes: accessing the source code of a script hosted by a remote server; extracting features from the source code in accordance with a machine-learning model comprising one or more layers of logic; at least based on the machine-learning model, determining, for each of the extracted features, a corresponding probability conditioned on the source code containing ransomware; and at least based on the machine-learning model, determining a combined probability for the extracted features conditioned on the source code containing ransomware when the extracted features are jointly present; comparing the combined probability with a threshold; in response to determining that the combined probability exceeds the threshold, flagging the source code as containing ransomware; and in response to determining that the combined probability does not exceed the threshold, flagging the source code as not containing ransomware.
A computer-implemented method for screening a source code for ransomware before the source code can be executed by a local computer, the method comprising:
A computer system for screening a source code for ransomware, the computer system comprising one or more processors configured to perform operations of:
A non-transitory computer-readable medium comprising software, which, when executed by a computer, causes the computer to execute operations of:
Dependencies are inferred from the claim text.