## 8 Conclusions  
In this study, we conducted a review of the scheme by [PERSON] et al. and showed it fails to prevent security attacks, such as stolen mobile device, user impersonation, insider, sensor capture, and ESL attacks. Moreover, the scheme by [PERSON] et al. does not ensure \begin{table}
\begin{tabular}{c c} \hline \hline
**Scheme** & **Total Consumption (m)** \\ \hline [PERSON] et al. [32] & 5.298 \\ [PERSON] et al. [34] & 5.783 \\ [PERSON] et al. [35] & 5.854 \\ [PERSON] et al. [36] & 18.342 \\ [PERSON] et al. [37] & 4.614 \\ [PERSON] et al. [39] & 4.383 \\ [PERSON] et al. [15] & 3.009 \\ Proposed & 3.939 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Energy consumption of IoT sensors. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Security Feature** & [32] & [34] & [35] & [36] & [37] & [39] & [15] & **Proposed** \\ \hline \(S_{1}\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\times\) & \(\circ\) \\ \(S_{2}\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\times\) & \(\circ\) \\ \(S_{3}\) & \(\times\) & \(\times\) & \(\circ\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\circ\) \\ \(S_{4}\) & \(\circ\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\circ\) \\ \(S_{5}\) & \(\times\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\times\) & \(\circ\) \\ \(S_{6}\) & \(\times\) & - & \(\circ\) & - & \(\times\) & - & \(\times\) & \(\circ\) \\ \(S_{7}\) & \(\circ\) & \(\times\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) \\ \(S_{8}\) & \(\circ\) & \(\times\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) \\ \(S_{9}\) & \(\circ\) & - & - & \(\times\) & - & \(\circ\) & \(\circ\) \\ \(S_{10}\) & \(\times\) & - & \(\circ\) & \(\circ\) & \(\circ\) & \(\times\) & \(\circ\) & \(\circ\) \\ \(S_{11}\) & \(\times\) & \(\times\) & \(\circ\) & \(\circ\) & \(\circ\) & - & \(\times\) & \(\circ\) \\ \(S_{12}\) & \(\circ\) & \(\circ\) & - & \(\circ\) & \(\circ\) & \(\circ\) & - & \(\circ\) \\ \(S_{13}\) & \(\circ\) & \(\times\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\times\) & \(\circ\) \\ \(S_{14}\) & \(\times\) & \(\times\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\circ\) & \(\times\) & \(\circ\) \\ \(S_{15}\) & \(\circ\) & \(\circ\) & - & \(\circ\) & \(\circ\) & \(\circ\) & \(\times\) & \(\circ\) \\ \hline \hline \end{tabular} \(\times\): No guarantee, \(\circ\): Guarantee, -: Not considered  
\end{table} 
Table 8: Security features. user untraceability. We propose a secure and privacy-preserving authentication scheme for a smart farming environment to overcome the weakness of [PERSON] et al. 's scheme. Our scheme employs only the XOR operation, hash function, and PUF, considering the limited resources of IoT sensors commonly used in smart farming environments. The proposed scheme achieves the security demands for smart farming and resists numerous security attacks, including stolen mobile device, insider, sensor capture, and replay attacks. We formally verified the security of our scheme using \"BAN logic\" to ensure mutual authentication, the \"RoR model\" to validate the robustness of the session key, and the \"AVISPA simulation tool\" to demonstrate resilience to replay and MITM attacks. In addition, we demonstrated that our scheme has light computational and communication overheads. In comparison with related schemes regarding the computational cost, communication cost, and security features, our scheme offers more security features with a lower overhead; hence, it is the most efficient in terms of both cost and security. In future work, we aim to apply our scheme to real-world smart farming environments to evaluate its scalability and develop a more practical authentication protocol.