Machine Learning Based Cross-Language Vulnerability Detection : How Far Are We

Date

2020-05

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Abstract

This thesis concerns the study of Machine Learning based methods for detecting vulnerable code. Various Neural Network models have been trained to detect specific vulnerabilities on a programming language dataset. This work, entails an approach not targeting specific vulnerabilities. We also leverage the commonality among programming languages like JAVA and C# by training the model on both languages and detecting vulnerabilities.

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Keywords

Machine learning, Computer security--Software, Source code (Computer science), Computer networks--Security measures--Software

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©2020 Anki Chauhan. All rights reserved.

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