CCS Concepts
• General and reference → Surveys and overviews 
• Security and privacy → Software security engineering 
• Computing methodologies → Machine learning; Neural networks;

1 INTRODUCTION

2 SURVEY OVERVIEW

2.1 Background and Scope of the Survey

2.2 Methodology

2.3 Taxonomy of Data-driven Software Vulnerability Assessment and Prioritization

3 EXPLOITATION PREDICTION

4 IMPACT PREDICTION

5 SEVERITY PREDICTION

6 TYPE PREDICTION

7 MISCELLANEOUS TASKS

8 ANALYSIS OF DATA-DRIVEN APPROACHES FOR SOFTWARE VULNERABILITY ASSESSMENT AND PRIORITIZATION

8.1 Data sources

8.2 Model features

8.3 Prediction models

8.4 Evaluation techniques

8.5 Evaluation metrics

9 OPEN RESEARCH CHALLENGES AND FUTURE DIRECTIONS OF DATA-DRIVEN SOFTWARE VULNERABILITY ASSESSMENT AND PRIORITIZATION

9.1 SV Data Availability

9.2 Real-world Application and Evaluation

9.3 Data-driven SV Assessment and Prioritization of Data-driven Systems

10 CONCLUSIONS