Objectives: This research work focuses on predicting traffic for the Smart City. Methods: Current research methods for traffic prediction are based on machine learning (ML) model. This article presents two contributions related to it. First, it provides feature engineering that includes feature extraction and a nature inspired optimization algorithm for selecting the best features. The mayfly optimization algorithm is improved by using the mode-based ranking method to select the best feature. Second, it uses the light-weight boosting method to train the datasets for better accuracy.Findings: The proposed Improved MayFly Optimization with LightGBM (IMFO-LGBM) is experimented with popular smart city datasets which is available in Kaggle website. IMFO-LGBM shows an improvement in the prediction accuracy when compared with the baseline methods. It shows 2% of increase in the overall accuracy. Novelty:Nature inspired Mayfly optimization is improved and used to find the best feature for prediction. The selected features are then trained with the light weight boosting algorithm (i.e., Light Gradient Boosting Model). The hybrid of improved mayfly optimization and light GBM outperformed well.
Objective: To propose an Intrusion Detection System, called SDPRM (Sinkhole Detection using Probe Route Mechanism), to distinguish sinkhole assaults on the steering administrations in IoT. Methods: SDPRM intends to moderate unfriendly impacts initiate in IDS which troubled the routine tasks. The proposed architecture has the node ranker, notoriety and trust systems for recognition of assailants by examining the way of behaving of gadgets. Probe routing mechanism along with cluster configuration of the IoT gadgets are used to detect the SH attack. The probability density function is used to detect the behaviour of the gadgets present in the IoT environment. To demonstrate the efficiency of the proposed work Cooja simulator is used for experimentation. Findings: The proposed SDPRM is compared with the existing INTI architecture and it shows good results for detection rate and packet delivery ratio parameters. The comparative analysis is performed for static and mobility scenario. Novelty: In the existing architecture, probe route protocol was not used to detect the sinkhole attack in IoT environment. The current research work uses FIB (Forwarding Information Base) based proberouting mechanism is used for securing the communication channel. The proposed architecture outperforms than the existing INTI architecture in terms of detection rate and packet delivery ratio.
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