A Trust-based Security and Privacy Protection for Data Collection in Smart City

Ensuring the genuineness and reliability of the data collected at the data collecting stage is of utmost importance in the Smart City (SC) industrial ecosystem. They influence the precision of statistical analysis and the impartiality of decision-making. Identifying attack behaviors caused by external interference and establishing a secure data transmission channel for terminals with limited resources are complex challenges. This paper presents a solution to these issues by introducing a Trust-based Security System (TSS). Within the framework of TSS, the initial step involves creating a trust model that utilizes binomial distribution to calculate the trust value of each node. The research implements a third-party suggestion method to enhance the objective of the trust rating. The research provides a trust management strategy to mitigate the ON-OFF assault. The study develops a robust routing algorithm that effectively manages the trade-off between safety, transmission effectiveness, and energy consumption. A comprehensive simulation exercise assesses the analytical findings of the TSS.