# AgriSecure: A Fog Computing-Based Security Framework for Agriculture 4.0 via Blockchain
## 5 Existing Research on Security in Agriculture 4.0
A development board for the ESP8266 maker focus When a Raspberry Pi is attached, WiFi Deauther Monster is used to disconnect it from the network and stop sensor data from being transferred to a distant cloud. The notion of Activity-Centric Access Control (ACAC) for smart and connected ecosystems was first proposed by [PERSON], [PERSON] et al. in [105] and discussed in this article as a first step. Here, they examined the idea of activity with regard to cooperative and dispersed yet interconnected systems, identifying the many parties involved as well as the crucial elements to consider when making an activity control choice. They provide an initial framework for developing activity control expressions that may be used by various smart objects in the system. The biggest obstacle to the growth of cloud computing is security worries. Information security continues to have an impact on the market even though it raises inconveniences related to information security. The threat of security breaches in the cloud infrastructure must be understood by clients. Cloud-computing capacity, networking, and computing powers are brought to the edge by fog computing. One of the most critical challenges with fog computing platforms is safety and security. Lightweight devices have benefited greatly from edge computing's ability to complete difficult tasks quickly, but the technology's hasty development has led to a general disregard for safety risks in edge computing stages and the applications they allow. In our proposed framework we have focused on the threats in fog computing-based IoT environment via blockchain for the application in agriculture 4.0. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**References** & **Years** & **Scenario** & **Technology \& Security** \\ \hline
[73,75,92] & (2022–2023) & Smart equipment, Smart irrigation & Automation, IoT \\  & & & Theft detection by motion detector \\ \hline
[84,97] & (2019, 2021) & Efficient and secure cluster routing for IoT-based smart agriculture applications & WSNs, data encryption A strong communication channel and symmetrical data security for security between farming devices \\ \hline
[35,95] & (2021, 2023) & Supply Chain Tracking, Aerial Crop Management, Livestock Safeness, and Maturity Tracking, and Irrigation & Smart agriculture IoT \\ \hline
[76,87,93] & (2019–2021) & Security and privacy in green-IoT-based agriculture & Blockchain, IoT \\ \hline
[106] & (2021) & Ecosystem for smart agriculture & Authenticating IoT sensor device and sending encrypted data \\ \hline
[79,100] & (2021, 2023) & Intelligent and secure smart irrigation system & IoT, blockchain \\  & & & Decentralized storage of irrigation and plants database by implementing the concept of blockchain \\ \hline
[48,96] & (2018, 2020) & Precision agriculture threat prediction model based on Common Vulnerability Scoring System & Parameters detection, IoT system A prediction model framework for cyber-attacks in precision agriculture \\ \hline
[68,94] & (2021, 2020) & Precision agriculture-based multilayered security and privacy architecture & IoT, AI \\  & & & A holistic study on security and privacy in a smart agriculture ecosystem \\ \hline
[59,91] & (2021, 2019) & Swarm robotic systems for precision farming & Blockchain \\  & & & Public key cryptography by blockchain \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Related Research performed on Security issues in Agriculture 4.0.