# Cyber-Security Threats and Side-Channel Attacks for Digital Agriculture
## 2 Digital Agriculture  
Agriculture is the lifeline of humans and provides not only food, but also generates employment. The high demand and sustainable food production, shortage of skills, and efficient use of limited environmental resources demand the modernisation of the centuries-old agricultural sector. Digital agriculture (DigAg) (also called smart agriculture/farming) is the use of various digital devices to monitor, assess, and manage environmental parameters that could affect food production (crops, fruit, etc.) [2]. The environmental parameters could be soil condition, water use, moisture content, plant and crop diseases, weather conditions, pests, pollination, nutrition, and the irrigation system. Digital devices such as smartphones, various sensors, global position systems (GPSs), robotics, and drones could be utilised to extract valuable data and analyse and make effective decisions to increase food production with less human resources and intervention.  
Figure 1 shows an overview of digital agriculture and its various components. Broadly, it can be split into four separate layers.  
1. Layer 1 is a sensing layer with different sensors to monitor the plants or environmental factors ranging from soil to weather conditions. Sensors would vary for different applications and use cases. These sensors are typically inexpensive, have small computation and battery power, are deployed in the field, and are primarily unattended in a hostile environment. The same layer can have actuator functionalities to perform a specific operation, such as water control or spraying via drones.
2. Layer 2 is the gateway layer, where gateways provide an interface between the Internet and sensors. Typically, wireless communication is used to connect sensors. Depending on the application requirements, Zigbee, WiFi, Bluetooth, NB-IoT, Sigfox, LoRa, 5G, or satellite communication are used. The forwarding devices such as switches/access points are part of this layer.
3. Layer 3 is the storage or processing layer. An in-house data storage or cloud solution could be used.
4. Layer 4 is the application layer, where all the users see or control the sensors. Useful analytics are extracted from the data, and based on this, an informed action is performed. The end-user could be a farmer, an agroscientist, a broker, a trader, a government official, or a business.  
The standard IoT model combines Layers 3 and 4 into one layer and calls it the application layer. For digital agriculture, it should be split into two, as multiple users can use the same data for their individual purposes. Further splitting it into two layers makes the threat analysis easier and more accountable for data usage or malicious use.  
DigAg (pronounced \"Didge-Ag\") has several applications. Some are crop management, automation, precision agriculture [16], and monitoring activities. The latter include watching over or controlling irrigation and water quality [17], soil [18], weather, farm, pests, and diseases [19]. The subsequent sections highlight the use of DigAg in smart irrigation [20] and intelligent machinery [21], discussing some of the threats that malicious actors could exploit.