## 2 Related Work
[36] introduced a signature-based anonymous user authentication scheme that relies on ECC. However, this scheme suffers from a high computational overhead and does not prevent sensor impersonation attacks. Specifically, the transition of ECC-based signatures incurs high communication overheads. Due to the high computational and communication overheads of ECC, these schemes are unsuitable for smart farming systems with constrained resources. Therefore, a variety of resource-efficient authentication schemes have been presented by researchers. For example, a lightweight authentication scheme for IoT-based environments was developed by [PERSON] et al. [37]. Although designed for devices with limited resources, the scheme incurs a high communication overhead and remains vulnerable to sensor impersonation, insider, and sensor capture attacks. Moreover, the scheme also does not guarantee perfect forward secrecy [38]. Similarly, [PERSON] et al. [39] developed an authentication protocol for a WSN with limited-resource sensors. Although it achieves a low computational overhead, it imposes high communication costs and does not resist replay, sensor capture, impersonation, and insider attacks [40]. [PERSON] et al. [15] offered a lightweight, privacy-preserving authentication scheme for rural smart farm monitoring systems using only XOR operations and hash functions. Despite its simplicity, the scheme is vulnerable to sensor capture, insider, stolen mobile device, and ESL attacks. Moreover, this scheme fails to ensure user untraceability. A comparative summary of these related schemes is indicated in Table 1. \begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Schemes** & \multicolumn{2}{c}{**Contributions**} & \multicolumn{2}{c}{**Limitations**} \\ \hline
[22] & \(\bullet\) & Secure user authentication scheme for agriculture monitoring. Use a fuzzy extractor and bio-hash function. & \(\bullet\) & Vulnerable to insider and sensor node impersonation attacks. Does not guarantee perfect forward secrecy. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of the related work. \begin{table}
\begin{tabular}{l c c c} \hline \hline
**Schemes** & \multicolumn{2}{c}{**Contributions**} & **Limitations** \\ \hline
[23] & \(\bullet\) & Lightweight authentication scheme for \(\bullet\) & Vulnerable to stolen mobile device, agriculture monitoring. & privileged insider, and ESL attacks. \\  & \(\bullet\) & Based on dynamic pseudonym identity. & \\ \hline
[25] & \(\bullet\) & Lightweight authentication scheme for \(\bullet\) & Cannot retrieve due to lack of user information. \\  & \(\bullet\) & Based on ECC. & \\ \hline
[26] & \(\bullet\) & Secure authentication scheme for agriculture. & \(\bullet\) & Cannot retrieve due to lack of user information. \\  & \(\bullet\) & Based on ECC. & \\ \hline
[27] & \(\bullet\) & User authentication scheme for a WSN. & \(\bullet\) & Vulnerable to ESL attacks. \\  & \(\bullet\) & Uses a fuzzy extractor. & \\ \hline
[28] & \(\bullet\) & Secure and efficient user authentication & \(\bullet\) & Vulnerable to ESL attacks. \\  & \(\bullet\) & scheme for a WSN. & \\  & \(\bullet\) & Based on XOR operations and hash functions. & \\ \hline
[29] & \(\bullet\) & Secure three-factor authentication scheme for a WSN. & \(\bullet\) & Vulnerable to MITM and privileged insider attacks. \\  & \(\bullet\) & Uses a Chebyshev chaotic mapping. & \(\bullet\) & Does not guarantee perfect forward secrecy. \\ \hline
[30] & \(\bullet\) & Three-factor authentication scheme for a WSN. & \(\bullet\) & High computational cost. \\  & \(\bullet\) & Based on ECC. & \\ \hline
[31] & \(\bullet\) & User authentication scheme for a WSN. & \(\bullet\) & Vulnerable to stolen verifier attacks. \\  & \(\bullet\) & Uses a fuzzy extractor. & \(\bullet\) & Does not guarantee perfect forward secrecy. \\ \hline
[32] & \(\bullet\) & Efficient authentication scheme for a WSN. & \(\bullet\) & Vulnerable to ESL and privileged insider attacks. \\  & \(\bullet\) & Based on ECDH.