# Advanced Persistent Threats and Their Defense Methods in Industrial Internet of Things: A Survey
## 4 APT Analysis Model
### Model Comparison  
Through the detailed description of the six models above, we summarize that the advantage of the threat intelligence model [74; 75] is that it can provide targeted and practical threat intelligence information and help organizations formulate effective security strategies and measures, and its disadvantage is that it relies on external sources of information, which may lead to the low quality, timeliness, and reliability of the information. The application of the threat intelligence model to defend against APT attacks lies in the fact that it can help organizations obtain and use the threat intelligence information of APT attacks in time, thereby improving the early warning and response capabilities for APT attacks. The advantage of the attack chain model [81; 82; 83; 84; 85; 86] is that it can provide a clear and complete view of the attack process and help organizations take corresponding defense measures at different stages, and its disadvantage is that it may not cover all types and changes of attack methods and may also be identified and avoided by attackers. The application of the attack chain model to defend against APT attacks lies in the fact that it can help security personnel analyze the behavior and purpose of attackers. The advantage of the diamond model [87; 88; 89] is that it can provide a comprehensive and dynamic view of competitive analysis and help organizations discover their own and others' strengths and weaknesses, and its disadvantage is that it may ignore some important factors, such as government policies, cultural differences, and international cooperation. The application of the diamond model to defend against APT attacks lies in the fact that it can help organizations understand the various factors that affect APT activities. The advantage of the risk assessment model [93; 94; 95; 96] is that it can provide a systematic and scientific view of risk management and help organizations formulate reasonable and effective risk control measures, and its disadvantage is that it may be affected by data quality, assessment methods, human factors, etc., resulting in inaccurate or incomplete assessment results. The ability of the risk assessment model to defend against APT attacks lies in the fact that it can help organizations assess and control the risks associated with APT attacks. The advantage of the machine learning model [101; 102; 103; 104; 105; 106] is that it can provide an efficient and flexible view of data analysis, help organizations discover hidden information and value in data, and its disadvantage is that it may be affected by data quality, algorithm selection, model training, etc., resulting in poor or unstable model performance. The application of the machine learning model to defend against APT attacks lies in the fact that it can help organizations process and use large and diverse data, such as network traffic, log files, and threat intelligence, thereby improving the detection and analysis capabilities for APT attacks. The advantage of the network simulation model [107; 108; 109] is that it can provide a controllable and repeatable network experiment environment and help organizations analyze and understand the interaction between different network components and devices, and its disadvantage is that it may not fully reflect all factors and situations in real networks and may also have some errors and biases. The application of the network simulation model to defend against APT attacks lies in the fact that it can help organizations design and verify new network protocols, algorithms, architectures, etc., thereby improving their defense capabilities against APT attacks. In order to better and more intuitively understand these six models, we list their advantages, disadvantages, and applications in Table 5.