## 5 Research Directions
### Security and Privacy  
DT applications rely on data provided by IoT sensors and gateways. In this case, data and communication security and privacy are an important research direction. In considering security, we discuss the research from several perspectives: confidentiality, integrity, and availability.  
In terms of confidentiality, we now take the smart transportation system as an example. DT obtains data from IoT sensors installed near roads, vehicles, etc. At the same time, IoT sensors may belong to different organizations/operators. In this case, different organizations/operators need to ensure the confidentiality of data through some authentication and secured communication protocols. In addition, some data stored in the application layer, such as vehicle location and traffic camera data, are sensitive. Thus, access control needs to be in place to protect user privacy. At the same time, some information security regulations can protect user privacy and achieve data confidentiality by restricting data sharing, especially on the end-user layer. For example, in the field of healthcare, Health Insurance Portability and Accountability Act (HIPPA) will be used to regulate the sharing and confidentiality of user medical data.  
For the sake of integrity, some DT applications, including smart grid, smart transportation, smart manufacturing, and smart cities, require real-time data to build a digital model of the DT system. In this case, data integrity is essential for the DT system to correctly model and guide the physical system in response to changes in the environment. Based on the DT architecture, we discuss the integrity of the four layers. For the object layer,the sensors need to communicate with the gateways. In this case, the communication from sensor to gateway and gateway to sensor at the application layer needs to be secured to prevent an adversary from hijacking the communication using a man-in-the-middle (MITM) attack or others. In addition, authentication and other security mechanisms must be in place to restrict unauthorized users from modifying data. At the same time, at the application layer, anomaly detection can be used to detect manipulated data to ensure data integrity. Finally, an authentication system can be implemented at the end user level to prevent unauthorized users from accessing DT.  
Finally, availability is key to real-time DT. Certain types of cyber attacks, including distributed denial of service (DDoS) and malware propagation, can target sensors and gateways. In this case, mitigation schemes need to be implemented on the gateways to filter malicious traffic and reduce the impact of attacks. At the same time, an adversary can send time-consuming queries or massive queries through the end user layer to overload the DT. To deal with such threats, mitigation schemes can be deployed at the application layer to avert the affects. Moreover, in a certain period of time, there may be multiple normal users accessing the same service at the same time. In this case, load balancing algorithms can be deployed on the gateway. If a gateway is overloaded, the algorithm can use nearby low-load gateways to process the request, leading to a highly resilient system.