Today, farmers are suffering from the low yield of crops. Though right crop selection is the main boosting key to maximize crop yield by doing soil analysis and considering metrological factors, the lack of knowledge about soil fertility and crop selection is the main reason for low crop production. In the changed current climate, the farmers having primitive knowledge about conventional farming are facing challenges about making sagacious decisions on crop selection. The selection of the same crop in every seasonal cycle makes the low soil fertility. This study is aimed at making an efficient and accurate system using IoT devices and machine learning (ML) algorithms that can correctly select a crop for maximal yield. Such a system is reliable as compared to the old laboratory testing manual systems, which bear the chances of human errors. Correct selection of a crop is predominantly a priority in agricultural arena. As a contribution, we propose an ML-based model, Smart Crop Selection (SCS), which is based on data of metrological and soil factors. These factors include nitrogen, phosphorus, potassium, CO2, pH, EC, temperature, humidity of soil, and rainfall. Existing IoT-based systems are not efficient as compared to our proposed model due to limited consideration of these factors. In the proposed model, real-time sensory data is sent to Firebase cloud for analysis. Its results are also visualized on the Android app. SCS ensembles the following five ML algorithms to increase performance and accuracy: Decision tree, SVM, KNN, Random Forest, and Gaussian Naïve Bayes. For rainfall prediction, a dataset containing historical data of the last fifteen years is acquired from Bahawalpur Agricultural Department. This dataset and an ML algorithm, Multiple Linear Regression leverages prediction of the rainfall in future, a much-desired information for the health of any crop. The Root Mean Square Error of the rain fall prediction model is 0.3%, which is quite promising. The SCS model is trained for 11 crops’ prediction, while its accuracy is 97% to 98%.

The Internet of Drones (IoD) has recently gained popularity in several military, commercial, and civilian applications due to its unique characteristics, such as high mobility, three-dimensional (3D) movement, and ease of deployment. Drones, on the other hand, communicate over an unencrypted wireless link and have little computational capability in a typical IoD environment, making them exposed to a wide range of cyber-attacks. Security vulnerabilities in IoD systems include man-in-the-middle attacks, impersonation, credential leaking, GPS spoofing, and drone hijacking. To avoid the occurrence of such attacks in IoD networks, we need an extremely powerful security protocol. To address these concerns, we propose a blockchain-based authentication scheme employing Hyperelliptic Curve Cryptography (HECC). The concepts of a blockchain as a Certificate Authority (CA) and a transaction as a certificate discussed in this article are meant to facilitate the use of a blockchain without CAs or a Trusted Third Party (TTP). We offer a security analysis of the proposed scheme, which demonstrates its resistance to known and unknown attacks. The proposed scheme resists replay, man-in-the-middle, device impersonation, malicious device deployment, Denial-of-Service (DoS), and De-synchronization attacks, among others. The security and performance of the proposed scheme are compared to relevant existing schemes, and their performance is shown to be better in terms of security attributes as well as computation and communication costs than existing competitive schemes. The total computation cost of the proposed scheme is 40.479 ms, which is 37.49% and 49.79% of the two comparable schemes. This shows that the proposed scheme is better suited to the IoD environment than existing competitive schemes.

The Internet of Vehicles (IoVs) is a wireless network of intelligent and autonomous vehicles and Roadside Units (RSUs), which work together to improve transportation services. On the one hand, this revolutionary mode of transportation optimizes traffic efficiency and reduces congestion and accidents; on the other hand, it raises security and privacy concerns. As a result, keeping the security and privacy aspects of such vital systems should be a top concern, as security and privacy flaws can have devastating implications. In addition, each vehicle's on-board unit (OBU) has a certain amount of processing and storage power. As a result, in areas with high traffic density, vehicles that need to verify messages have a very high computational overhead. In this article, we propose a conditional privacy-preserving heterogeneous signcryption scheme for IoV utilizing Hyperelliptic Curve Cryptography (HECC) operation. The security robustness of the proposed scheme has been evaluated with the Random Oracle Model (ROM), a formal security evaluation method. In addition, relevant existing schemes are compared to the proposed scheme in terms of computation and communication costs. The findings demonstrate that the proposed scheme is both efficient and secure, validating its viability.

Thanks to the widespread availability of Fifth Generation (5G) wireless connectivity, it is now possible to provide preventative or proactive healthcare services from any location and at any time. As a result of this technological improvement, Wireless Body Area Networks (WBANs) have emerged as a new study of research in the field of healthcare in recent years. WBANs, on the one hand, intend to gather and monitor data from the human body and its surroundings; on the other hand, biomedical devices and sensors interact through an open wireless channel, making them exposed to a range of cyber threats. However, WBANs are a heterogeneous-based system; heterogeneous cryptography is necessary, in which the transmitter and receiver can employ different types of public key cryptography. This article proposes an improved and efficient heterogeneous authentication scheme with a conditional privacy-preserving strategy that provides secure communication in WBANs. In the proposed scheme, we employed certificateless cryptography on the client side and Identity-Based Cryptography on the receiver side. The proposed scheme employs Hyperelliptic Curve Cryptography (HECC), a more advanced variation of Elliptic Curve Cryptography (ECC). HECC achieves the same level of security with a smaller key size and a more efficient approach than its counterpart methods. The proposed scheme not only meets the security and privacy standards of WBANs but also enhances efficiency in terms of computation and communication costs, according to the findings of the security and performance analysis.