# Hyperledger Fabric Access Control for Industrial Internet of Things
## 2 Preliminary
### Internet of Things  
In 1995, [PERSON] proposed the concept of the Internet of Things in \"The Road to the Future\". The term Internet of Things was first proposed in 1999 by [PERSON] of the Automatic Identification Center of the Massachusetts Institute of Technology. The International Telecommunication Union (International Telecommunication Union, ITU) formally proposed the concept of the Internet of Things (IoT) in 2005. Later, in 2009, IBM proposed the concept of \"Smart Earth\". The Internet of Things (IoT) once again attracted widespread attention from all walks of life. The Internet of Things consists of actual objects, such as home appliances, machines, vehicles, etc., along with embedded sensors and APIs, and other devices, to form information connection and network exchange [8].  
[PERSON] [12] published the seven-layer architecture at the Internet of Things World Forum. The functions of each layer are described below:  
* Physical Devices and Controllers: Multiple physical devices and controllers are considered as \"Things\" in the Internet of Things. There exist all types of sensors, devices, machines, or intelligent edge nodes, to receive and transmit data between terminal equipment.
* Connectivity: The most important factor of IoT is the connectivity with reliable and instant data transmission. Different technology has been explored to propagate data such as radio frequency identification (RFID), cellular networks (4G/5G), Wi-Fi, Bluetooth, ZigBee, routers, and switches.  
* Edge Computing: Edge computing is a decentralized computing architecture, where a huge number of services are processed by a central node to divide into smaller tasks and distribute to edge nodes for processing. The edge node is close to the terminal device, which can make the transmission speed and data processing faster and reduce the delay. It is suitable for processing big data. Edge software has many service applications, and some can be completely independent of vertical applications. The most typical application is Microsoft's Cognitive Service, an intelligent data analysis model based on Azure's machine learning. Setting up edge nodes in the place closest to the data source can provide the computing power of the cognitive service data analysis model. Without the need to send data to the cloud, costs on transmission time and analysis results can be reduced.
* Data Accumulation: Data accumulation is to convert real-time data to static format, filter, and reduce the amount of data before being sent to database storage. The stored data can then be used by the other applications when it is not timely.
* Data Abstraction: Data abstraction unifies data formats from different databases and integrates them into the same place. Identity verification and authorization could be used to protect data through regularization, and indexing could provide quick access.
* Applications: Applications on personal computers, smart devices, and other equipment could verify data analysis results, receive early warning notifications, and provide the correct information to support users on decision makings and actual actions.
* Collaborations and Processes: Collaborations and processes are critical in IoT since most actions require the involvement of multiple devices and users.