1 INTRODUCTION  
2 PRELIMINARIES  
2.1 Notations  
2.2 Background of Machine Unlearning  
2.3 Techniques of Machine Unlearning  
2.4 Privacy Risk of Machine Learning and Unlearning  
3 MACHINE UNLEARNING TECHNIQUES AND VULNERABILITIES  
3.1 Data-oriented Techniques  
3.2 Model-oriented Techniques  
4 PRIVACY THREATS OF MACHINE UNLEARNING  
4.1 Information-stealing Attacks  
4.2 Model-breaking Attacks  
4.3 Attack-oriented Metrics  
4.4 Possible Defense Methods for Unlearning Attacks  
5 MACHINE UNLEARNING APPLICATIONS WITH PRIVACY THREATS  
5.1 Unlearning in Large Language Models  
5.2 Unlearning in Federated Learning  
5.3 Unlearning in Anomaly Detection  
5.4 Discussion and Privacy Vulnerability of Unlearning Applications  
6 DISCUSSION AND FUTURE DIRECTIONS  
6.1 The Design of Machine Unlearning  
6.2 The Vulnerability of Machine Unlearning  
6.3 The Evaluation of Machine Unlearning  
6.4 The Applications of Machine Unlearning