1 INTRODUCTION

2 PRELIMINARIES OF DATA PRIVACY, ATTACKS AND DEEP LEARNING ON GRAPHS

3 ATTACKS ON GRAPH NEURAL NETWORKS (GNNS)

4 PRIVACY PRESERVATION TECHNIQUES ON GNNS

5 DATASETS AND APPLICATIONS

6 FUTURE DIRECTIONS

7 CONCLUSION