Predicting code vulnerabilities using machine learning classifier models trained on internal analysis states

Predicting code vulnerabilities using machine learning classifier models trained on internal analysis states

An example system includes a processor to receive a source code sample to be classified. The processor can execute a hybrid code analysis to generate an internal analysis state. The processor can extract features from the internal analysis state via a trained machine learning model modified using tr...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Copty, Fady, Doron, Shai, Igbaria, Reda
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Beschreibung
Zusammenfassung:An example system includes a processor to receive a source code sample to be classified. The processor can execute a hybrid code analysis to generate an internal analysis state. The processor can extract features from the internal analysis state via a trained machine learning model modified using transfer learning. The processor can generate a label based on the extracted features via a machine learning classifier model trained on internal analysis states of hybrid code analyses.