# Cyber-Security Threats and Side-Channel Attacks for Digital Agriculture
## 2 Digital Agriculture
### Application--Intelligent Machinery in Agriculture  
An intelligent agricultural machine can use sensors and computer logic to control and operate the equipment to achieve a defined goal on the ground with minimum human intervention. A large agricultural paddock can be divided into small plots for cultivation. The soil, moisture, precise seed planting, and land level variances make it difficult to achieve maximum productivity with limited manual or semi-autonomous resources. For example, analysing the soil and moisture contents in real-time and precisely applying fertiliser or other chemicals based on need are time-consuming in a manual operation and are dependent on the skilled farmer. An intelligent machine fills the skill gap and works virtually 24/7. It could be used in all aspects of agricultural tasks such as seed planting on waterways, harvesting, applying fertilisers, monitoring the health of crops, and levelling and ploughing the fields.  
A fully automated system should have the intelligence to know its precise location, find the path, be equipped with a safety system, and activate monitoring, analysis, and actuation related to cultivation. The intelligence can be achieved by integrating different sensors, actuators, and communication systems. The attack surface spans multiple systems, and exploiting a vulnerability in any part of the machinery could have devastating effects. For example, substandard soil analysis could result in faulty application of chemicals/fertiliser, which will have long-term effects on the productivity of the agricultural field. In some  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Sensing/Actuation** & **Gateway** & **Storage** & **User** \\ \hline Description & Threats are related to & Threats are related to & Threats are related to & The end-user interface \\  & hardware, physical & data in transit and & data at rest, either in & is at Layer 4, and the \\  & access, damage, & involve network & the cloud or & compromise of \\  & firmware/ hardware & devices and & on-premises. The & credentials through \\  & modification, or the & communication & compromise of data & social engineering or \\  & wrong actuation to & protocols. & could lead to IP theft. & malware injection \\  & destroy crops. & Vulnerabilities can be & could compromise the \\  & & exploited to sniff out & whole system. \\  & & and access data, & & \\  & & leading to diverse & & \\  & & attacks. & & \\ \hline Threats & Physical attacks, & Protocol & SQL injection, data & Social engineering, \\  & device/sensor or & vulnerabilities [25], & privacy, IP theft, & phishing, access \\  & firmware & authentication, MIM, & encryption, & control, service \\  & alteration [22], & interference, & confidentiality and & interruption, insider \\  & side-channel attacks, & firmware [26], & routing, & integrity, cloud & attacks \\  & eavesdropping [23], & jamming [27], & malware injection [28], & \\  & booting, physical & DoS/DDoS, sniffing & misconfiguration, & \\  & damage, malicious & attacks & flooding attacks in the & \\  & code, forgery, sleep & & cloud [29] & \\  & deprivation attacks [24] & & & \\ \hline \hline \end{tabular} Countermeasures  
* Periodic assessment of devices including vulnerabilities, auditing, penetration testing
* Firmware/software update mechanism to patch security vulnerabilities
* End-to-end encrypted communication including encrypted drives to keep data inaccessible in the case of device theft
* Two-factor authentication and secure password recovery mechanisms
* Block unnecessary services and ports on the devices
* Avoid device tampering with a physically unclonable function
* Adaption of a zero-trust model assuming a perimeter-less network  
\end{table}
Table 1: Typical threats to digital agriculture and countermeasures.  
cases, it might not be noticeable even after many weeks, which would make the rectification difficult both in terms of time and money.