Accepted Publication

Our paper, A Survey of Source Code Representations for Machine Learning-Based Cybersecurity Tasks, was accepted for publication in ACM Computing Surveys! In this work, we systematically review how source code is represented in ML-based cybersecurity research. Data representation is a key part of the ML pipeline and understanding what each representation offers in terms of feature information allows researchers to choose or create a representation that best suits their needs.