The Routing Protocol for Low-Power and Lossy Networks (RPL) is a widely adopted protocol for managing and optimizing routing in resource-constrained Internet of Things (IoT) environments.  RPL operates by constructing a Destination-Oriented Directed Acyclic Graph (DODAG) to establish efficient routes between nodes. This protocol is designed to address the unique challenges of IoT networks, such as limited energy resources, unreliable wireless links, and frequent topology changes. RPL's adaptability and scalability render it particularly suitable for large-scale IoT deployments in various applications, including smart cities, industrial automation, and environmental monitoring. However, the protocol's vulnerability to various security attacks poses significant threats to the reliability and confidentiality of IoT networks. To address this issue, a novel deep-stacked neuro-fuzzy system (DSNFyS) has been developed for attack detection in RPL-based IoT. The proposed approach begins with simulating RPL routing in IoT, followed by attack detection processing at the Base Station (BS) using log data. Data normalization is accomplished through the application of min-max normalization techniques. The most crucial features are then identified through feature selection, utilizing information gain and Support Vector Machine-Recursive Feature Elimination (SVM-RFE). Attack detection is subsequently performed using DSNFyS, which integrates a Deep Stacked Autoencoder (DSA) with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Upon detection of an attack, mitigation is carried out employing a DSA trained using the Hiking Optimization Algorithm (HOA). The proposed DSNFyS demonstrated exceptional performance, achieving the better accuracy of 97.41%, True Positive Rate (TPR) of 97.60%, and True Negative Rate (TNR) of 97.12%.

A wireless sensor network (WSN) is an emerging field comprising of sensor nodes as basic units. These sensor nodes have limited resources like power, memory etc. WSNs can be used to monitor the remote areas where recharging or replacing the battery power of sensor nods is not possible. This limitation of WSNs makes energy consumption as a most challenging issue. Low-Energy Adaptive Clustering Hierarchy (LEACH) is an easiest and first significant protocol which consumes less amount of energy while routing the data to the base station. A lot of work has been done to improve energy efficiency of routing protocol by taking LEACH as a base protocol. In this review paper section I has introduction to Wireless Sensor Networks, section II has introduction of LEACH Protocol and all descendant protocols of LEACH with comparison table have been discussed in section III.